MagickCore  7.1.0
Convert, Edit, Or Compose Bitmap Images
morphology.c
1 /*
2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3 % %
4 % %
5 % %
6 % M M OOO RRRR PPPP H H OOO L OOO GGGG Y Y %
7 % MM MM O O R R P P H H O O L O O G Y Y %
8 % M M M O O RRRR PPPP HHHHH O O L O O G GGG Y %
9 % M M O O R R P H H O O L O O G G Y %
10 % M M OOO R R P H H OOO LLLLL OOO GGG Y %
11 % %
12 % %
13 % MagickCore Morphology Methods %
14 % %
15 % Software Design %
16 % Anthony Thyssen %
17 % January 2010 %
18 % %
19 % %
20 % Copyright @ 2010 ImageMagick Studio LLC, a non-profit organization %
21 % dedicated to making software imaging solutions freely available. %
22 % %
23 % You may not use this file except in compliance with the License. You may %
24 % obtain a copy of the License at %
25 % %
26 % https://imagemagick.org/script/license.php %
27 % %
28 % Unless required by applicable law or agreed to in writing, software %
29 % distributed under the License is distributed on an "AS IS" BASIS, %
30 % WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
31 % See the License for the specific language governing permissions and %
32 % limitations under the License. %
33 % %
34 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
35 %
36 % Morphology is the application of various kernels, of any size or shape, to an
37 % image in various ways (typically binary, but not always).
38 %
39 % Convolution (weighted sum or average) is just one specific type of
40 % morphology. Just one that is very common for image bluring and sharpening
41 % effects. Not only 2D Gaussian blurring, but also 2-pass 1D Blurring.
42 %
43 % This module provides not only a general morphology function, and the ability
44 % to apply more advanced or iterative morphologies, but also functions for the
45 % generation of many different types of kernel arrays from user supplied
46 % arguments. Prehaps even the generation of a kernel from a small image.
47 */
48 ␌
49 /*
50  Include declarations.
51 */
52 #include "MagickCore/studio.h"
53 #include "MagickCore/artifact.h"
54 #include "MagickCore/cache-view.h"
55 #include "MagickCore/channel.h"
56 #include "MagickCore/color-private.h"
57 #include "MagickCore/enhance.h"
58 #include "MagickCore/exception.h"
59 #include "MagickCore/exception-private.h"
60 #include "MagickCore/gem.h"
61 #include "MagickCore/gem-private.h"
62 #include "MagickCore/image.h"
63 #include "MagickCore/image-private.h"
64 #include "MagickCore/linked-list.h"
65 #include "MagickCore/list.h"
66 #include "MagickCore/magick.h"
67 #include "MagickCore/memory_.h"
68 #include "MagickCore/memory-private.h"
69 #include "MagickCore/monitor-private.h"
70 #include "MagickCore/morphology.h"
71 #include "MagickCore/morphology-private.h"
72 #include "MagickCore/option.h"
73 #include "MagickCore/pixel-accessor.h"
74 #include "MagickCore/prepress.h"
75 #include "MagickCore/quantize.h"
76 #include "MagickCore/resource_.h"
77 #include "MagickCore/registry.h"
78 #include "MagickCore/semaphore.h"
79 #include "MagickCore/splay-tree.h"
80 #include "MagickCore/statistic.h"
81 #include "MagickCore/string_.h"
82 #include "MagickCore/string-private.h"
83 #include "MagickCore/thread-private.h"
84 #include "MagickCore/token.h"
85 #include "MagickCore/utility.h"
86 #include "MagickCore/utility-private.h"
87 ␌
88 /*
89  Other global definitions used by module.
90 */
91 #define Minimize(assign,value) assign=MagickMin(assign,value)
92 #define Maximize(assign,value) assign=MagickMax(assign,value)
93 
94 /* Integer Factorial Function - for a Binomial kernel */
95 #if 1
96 static inline size_t fact(size_t n)
97 {
98  size_t f,l;
99  for(f=1, l=2; l <= n; f=f*l, l++);
100  return(f);
101 }
102 #elif 1 /* glibc floating point alternatives */
103 #define fact(n) ((size_t)tgamma((double)n+1))
104 #else
105 #define fact(n) ((size_t)lgamma((double)n+1))
106 #endif
107 
108 
109 /* Currently these are only internal to this module */
110 static void
111  CalcKernelMetaData(KernelInfo *),
112  ExpandMirrorKernelInfo(KernelInfo *),
113  ExpandRotateKernelInfo(KernelInfo *, const double),
114  RotateKernelInfo(KernelInfo *, double);
115 ␌
116 
117 /* Quick function to find last kernel in a kernel list */
118 static inline KernelInfo *LastKernelInfo(KernelInfo *kernel)
119 {
120  while (kernel->next != (KernelInfo *) NULL)
121  kernel=kernel->next;
122  return(kernel);
123 }
124 
125 /*
126 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
127 % %
128 % %
129 % %
130 % A c q u i r e K e r n e l I n f o %
131 % %
132 % %
133 % %
134 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
135 %
136 % AcquireKernelInfo() takes the given string (generally supplied by the
137 % user) and converts it into a Morphology/Convolution Kernel. This allows
138 % users to specify a kernel from a number of pre-defined kernels, or to fully
139 % specify their own kernel for a specific Convolution or Morphology
140 % Operation.
141 %
142 % The kernel so generated can be any rectangular array of floating point
143 % values (doubles) with the 'control point' or 'pixel being affected'
144 % anywhere within that array of values.
145 %
146 % Previously IM was restricted to a square of odd size using the exact
147 % center as origin, this is no longer the case, and any rectangular kernel
148 % with any value being declared the origin. This in turn allows the use of
149 % highly asymmetrical kernels.
150 %
151 % The floating point values in the kernel can also include a special value
152 % known as 'nan' or 'not a number' to indicate that this value is not part
153 % of the kernel array. This allows you to shaped the kernel within its
154 % rectangular area. That is 'nan' values provide a 'mask' for the kernel
155 % shape. However at least one non-nan value must be provided for correct
156 % working of a kernel.
157 %
158 % The returned kernel should be freed using the DestroyKernelInfo() when you
159 % are finished with it. Do not free this memory yourself.
160 %
161 % Input kernel defintion strings can consist of any of three types.
162 %
163 % "name:args[[@><]"
164 % Select from one of the built in kernels, using the name and
165 % geometry arguments supplied. See AcquireKernelBuiltIn()
166 %
167 % "WxH[+X+Y][@><]:num, num, num ..."
168 % a kernel of size W by H, with W*H floating point numbers following.
169 % the 'center' can be optionally be defined at +X+Y (such that +0+0
170 % is top left corner). If not defined the pixel in the center, for
171 % odd sizes, or to the immediate top or left of center for even sizes
172 % is automatically selected.
173 %
174 % "num, num, num, num, ..."
175 % list of floating point numbers defining an 'old style' odd sized
176 % square kernel. At least 9 values should be provided for a 3x3
177 % square kernel, 25 for a 5x5 square kernel, 49 for 7x7, etc.
178 % Values can be space or comma separated. This is not recommended.
179 %
180 % You can define a 'list of kernels' which can be used by some morphology
181 % operators A list is defined as a semi-colon separated list kernels.
182 %
183 % " kernel ; kernel ; kernel ; "
184 %
185 % Any extra ';' characters, at start, end or between kernel defintions are
186 % simply ignored.
187 %
188 % The special flags will expand a single kernel, into a list of rotated
189 % kernels. A '@' flag will expand a 3x3 kernel into a list of 45-degree
190 % cyclic rotations, while a '>' will generate a list of 90-degree rotations.
191 % The '<' also exands using 90-degree rotates, but giving a 180-degree
192 % reflected kernel before the +/- 90-degree rotations, which can be important
193 % for Thinning operations.
194 %
195 % Note that 'name' kernels will start with an alphabetic character while the
196 % new kernel specification has a ':' character in its specification string.
197 % If neither is the case, it is assumed an old style of a simple list of
198 % numbers generating a odd-sized square kernel has been given.
199 %
200 % The format of the AcquireKernal method is:
201 %
202 % KernelInfo *AcquireKernelInfo(const char *kernel_string)
203 %
204 % A description of each parameter follows:
205 %
206 % o kernel_string: the Morphology/Convolution kernel wanted.
207 %
208 */
209 
210 /* This was separated so that it could be used as a separate
211 ** array input handling function, such as for -color-matrix
212 */
213 static KernelInfo *ParseKernelArray(const char *kernel_string)
214 {
215  KernelInfo
216  *kernel;
217 
218  char
219  token[MagickPathExtent];
220 
221  const char
222  *p,
223  *end;
224 
225  ssize_t
226  i;
227 
228  double
229  nan = sqrt((double)-1.0); /* Special Value : Not A Number */
230 
231  MagickStatusType
232  flags;
233 
235  args;
236 
237  kernel=(KernelInfo *) AcquireMagickMemory(sizeof(*kernel));
238  if (kernel == (KernelInfo *) NULL)
239  return(kernel);
240  (void) memset(kernel,0,sizeof(*kernel));
241  kernel->minimum = kernel->maximum = kernel->angle = 0.0;
242  kernel->negative_range = kernel->positive_range = 0.0;
243  kernel->type = UserDefinedKernel;
244  kernel->next = (KernelInfo *) NULL;
245  kernel->signature=MagickCoreSignature;
246  if (kernel_string == (const char *) NULL)
247  return(kernel);
248 
249  /* find end of this specific kernel definition string */
250  end = strchr(kernel_string, ';');
251  if ( end == (char *) NULL )
252  end = strchr(kernel_string, '\0');
253 
254  /* clear flags - for Expanding kernel lists thorugh rotations */
255  flags = NoValue;
256 
257  /* Has a ':' in argument - New user kernel specification
258  FUTURE: this split on ':' could be done by StringToken()
259  */
260  p = strchr(kernel_string, ':');
261  if ( p != (char *) NULL && p < end)
262  {
263  /* ParseGeometry() needs the geometry separated! -- Arrgghh */
264  (void) memcpy(token, kernel_string, (size_t) (p-kernel_string));
265  token[p-kernel_string] = '\0';
266  SetGeometryInfo(&args);
267  flags = ParseGeometry(token, &args);
268 
269  /* Size handling and checks of geometry settings */
270  if ( (flags & WidthValue) == 0 ) /* if no width then */
271  args.rho = args.sigma; /* then width = height */
272  if ( args.rho < 1.0 ) /* if width too small */
273  args.rho = 1.0; /* then width = 1 */
274  if ( args.sigma < 1.0 ) /* if height too small */
275  args.sigma = args.rho; /* then height = width */
276  kernel->width = (size_t)args.rho;
277  kernel->height = (size_t)args.sigma;
278 
279  /* Offset Handling and Checks */
280  if ( args.xi < 0.0 || args.psi < 0.0 )
281  return(DestroyKernelInfo(kernel));
282  kernel->x = ((flags & XValue)!=0) ? (ssize_t)args.xi
283  : (ssize_t) (kernel->width-1)/2;
284  kernel->y = ((flags & YValue)!=0) ? (ssize_t)args.psi
285  : (ssize_t) (kernel->height-1)/2;
286  if ( kernel->x >= (ssize_t) kernel->width ||
287  kernel->y >= (ssize_t) kernel->height )
288  return(DestroyKernelInfo(kernel));
289 
290  p++; /* advance beyond the ':' */
291  }
292  else
293  { /* ELSE - Old old specification, forming odd-square kernel */
294  /* count up number of values given */
295  p=(const char *) kernel_string;
296  while ((isspace((int) ((unsigned char) *p)) != 0) || (*p == '\''))
297  p++; /* ignore "'" chars for convolve filter usage - Cristy */
298  for (i=0; p < end; i++)
299  {
300  (void) GetNextToken(p,&p,MagickPathExtent,token);
301  if (*token == ',')
302  (void) GetNextToken(p,&p,MagickPathExtent,token);
303  }
304  /* set the size of the kernel - old sized square */
305  kernel->width = kernel->height= (size_t) sqrt((double) i+1.0);
306  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
307  p=(const char *) kernel_string;
308  while ((isspace((int) ((unsigned char) *p)) != 0) || (*p == '\''))
309  p++; /* ignore "'" chars for convolve filter usage - Cristy */
310  }
311 
312  /* Read in the kernel values from rest of input string argument */
313  kernel->values=(MagickRealType *) MagickAssumeAligned(AcquireAlignedMemory(
314  kernel->width,kernel->height*sizeof(*kernel->values)));
315  if (kernel->values == (MagickRealType *) NULL)
316  return(DestroyKernelInfo(kernel));
317  kernel->minimum=MagickMaximumValue;
318  kernel->maximum=(-MagickMaximumValue);
319  kernel->negative_range = kernel->positive_range = 0.0;
320  for (i=0; (i < (ssize_t) (kernel->width*kernel->height)) && (p < end); i++)
321  {
322  (void) GetNextToken(p,&p,MagickPathExtent,token);
323  if (*token == ',')
324  (void) GetNextToken(p,&p,MagickPathExtent,token);
325  if ( LocaleCompare("nan",token) == 0
326  || LocaleCompare("-",token) == 0 ) {
327  kernel->values[i] = nan; /* this value is not part of neighbourhood */
328  }
329  else {
330  kernel->values[i] = StringToDouble(token,(char **) NULL);
331  ( kernel->values[i] < 0)
332  ? ( kernel->negative_range += kernel->values[i] )
333  : ( kernel->positive_range += kernel->values[i] );
334  Minimize(kernel->minimum, kernel->values[i]);
335  Maximize(kernel->maximum, kernel->values[i]);
336  }
337  }
338 
339  /* sanity check -- no more values in kernel definition */
340  (void) GetNextToken(p,&p,MagickPathExtent,token);
341  if ( *token != '\0' && *token != ';' && *token != '\'' )
342  return(DestroyKernelInfo(kernel));
343 
344 #if 0
345  /* this was the old method of handling a incomplete kernel */
346  if ( i < (ssize_t) (kernel->width*kernel->height) ) {
347  Minimize(kernel->minimum, kernel->values[i]);
348  Maximize(kernel->maximum, kernel->values[i]);
349  for ( ; i < (ssize_t) (kernel->width*kernel->height); i++)
350  kernel->values[i]=0.0;
351  }
352 #else
353  /* Number of values for kernel was not enough - Report Error */
354  if ( i < (ssize_t) (kernel->width*kernel->height) )
355  return(DestroyKernelInfo(kernel));
356 #endif
357 
358  /* check that we recieved at least one real (non-nan) value! */
359  if (kernel->minimum == MagickMaximumValue)
360  return(DestroyKernelInfo(kernel));
361 
362  if ( (flags & AreaValue) != 0 ) /* '@' symbol in kernel size */
363  ExpandRotateKernelInfo(kernel, 45.0); /* cyclic rotate 3x3 kernels */
364  else if ( (flags & GreaterValue) != 0 ) /* '>' symbol in kernel args */
365  ExpandRotateKernelInfo(kernel, 90.0); /* 90 degree rotate of kernel */
366  else if ( (flags & LessValue) != 0 ) /* '<' symbol in kernel args */
367  ExpandMirrorKernelInfo(kernel); /* 90 degree mirror rotate */
368 
369  return(kernel);
370 }
371 
372 static KernelInfo *ParseKernelName(const char *kernel_string,
373  ExceptionInfo *exception)
374 {
375  char
376  token[MagickPathExtent] = "";
377 
378  const char
379  *p,
380  *end;
381 
383  args;
384 
385  KernelInfo
386  *kernel;
387 
388  MagickStatusType
389  flags;
390 
391  ssize_t
392  type;
393 
394  /* Parse special 'named' kernel */
395  (void) GetNextToken(kernel_string,&p,MagickPathExtent,token);
396  type=ParseCommandOption(MagickKernelOptions,MagickFalse,token);
397  if ( type < 0 || type == UserDefinedKernel )
398  return((KernelInfo *) NULL); /* not a valid named kernel */
399 
400  while (((isspace((int) ((unsigned char) *p)) != 0) ||
401  (*p == ',') || (*p == ':' )) && (*p != '\0') && (*p != ';'))
402  p++;
403 
404  end = strchr(p, ';'); /* end of this kernel defintion */
405  if ( end == (char *) NULL )
406  end = strchr(p, '\0');
407 
408  /* ParseGeometry() needs the geometry separated! -- Arrgghh */
409  (void) memcpy(token, p, (size_t) (end-p));
410  token[end-p] = '\0';
411  SetGeometryInfo(&args);
412  flags = ParseGeometry(token, &args);
413 
414 #if 0
415  /* For Debugging Geometry Input */
416  (void) FormatLocaleFile(stderr, "Geometry = 0x%04X : %lg x %lg %+lg %+lg\n",
417  flags, args.rho, args.sigma, args.xi, args.psi );
418 #endif
419 
420  /* special handling of missing values in input string */
421  switch( type ) {
422  /* Shape Kernel Defaults */
423  case UnityKernel:
424  if ( (flags & WidthValue) == 0 )
425  args.rho = 1.0; /* Default scale = 1.0, zero is valid */
426  break;
427  case SquareKernel:
428  case DiamondKernel:
429  case OctagonKernel:
430  case DiskKernel:
431  case PlusKernel:
432  case CrossKernel:
433  if ( (flags & HeightValue) == 0 )
434  args.sigma = 1.0; /* Default scale = 1.0, zero is valid */
435  break;
436  case RingKernel:
437  if ( (flags & XValue) == 0 )
438  args.xi = 1.0; /* Default scale = 1.0, zero is valid */
439  break;
440  case RectangleKernel: /* Rectangle - set size defaults */
441  if ( (flags & WidthValue) == 0 ) /* if no width then */
442  args.rho = args.sigma; /* then width = height */
443  if ( args.rho < 1.0 ) /* if width too small */
444  args.rho = 3; /* then width = 3 */
445  if ( args.sigma < 1.0 ) /* if height too small */
446  args.sigma = args.rho; /* then height = width */
447  if ( (flags & XValue) == 0 ) /* center offset if not defined */
448  args.xi = (double)(((ssize_t)args.rho-1)/2);
449  if ( (flags & YValue) == 0 )
450  args.psi = (double)(((ssize_t)args.sigma-1)/2);
451  break;
452  /* Distance Kernel Defaults */
453  case ChebyshevKernel:
454  case ManhattanKernel:
455  case OctagonalKernel:
456  case EuclideanKernel:
457  if ( (flags & HeightValue) == 0 ) /* no distance scale */
458  args.sigma = 100.0; /* default distance scaling */
459  else if ( (flags & AspectValue ) != 0 ) /* '!' flag */
460  args.sigma = QuantumRange/(args.sigma+1); /* maximum pixel distance */
461  else if ( (flags & PercentValue ) != 0 ) /* '%' flag */
462  args.sigma *= QuantumRange/100.0; /* percentage of color range */
463  break;
464  default:
465  break;
466  }
467 
468  kernel = AcquireKernelBuiltIn((KernelInfoType)type, &args, exception);
469  if ( kernel == (KernelInfo *) NULL )
470  return(kernel);
471 
472  /* global expand to rotated kernel list - only for single kernels */
473  if ( kernel->next == (KernelInfo *) NULL ) {
474  if ( (flags & AreaValue) != 0 ) /* '@' symbol in kernel args */
475  ExpandRotateKernelInfo(kernel, 45.0);
476  else if ( (flags & GreaterValue) != 0 ) /* '>' symbol in kernel args */
477  ExpandRotateKernelInfo(kernel, 90.0);
478  else if ( (flags & LessValue) != 0 ) /* '<' symbol in kernel args */
479  ExpandMirrorKernelInfo(kernel);
480  }
481 
482  return(kernel);
483 }
484 
485 MagickExport KernelInfo *AcquireKernelInfo(const char *kernel_string,
486  ExceptionInfo *exception)
487 {
488  KernelInfo
489  *kernel,
490  *new_kernel;
491 
492  char
493  *kernel_cache,
494  token[MagickPathExtent];
495 
496  const char
497  *p;
498 
499  if (kernel_string == (const char *) NULL)
500  return(ParseKernelArray(kernel_string));
501  p=kernel_string;
502  kernel_cache=(char *) NULL;
503  if (*kernel_string == '@')
504  {
505  kernel_cache=FileToString(kernel_string+1,~0UL,exception);
506  if (kernel_cache == (char *) NULL)
507  return((KernelInfo *) NULL);
508  p=(const char *) kernel_cache;
509  }
510  kernel=NULL;
511  while (GetNextToken(p,(const char **) NULL,MagickPathExtent,token), *token != '\0')
512  {
513  /* ignore extra or multiple ';' kernel separators */
514  if (*token != ';')
515  {
516  /* tokens starting with alpha is a Named kernel */
517  if (isalpha((int) ((unsigned char) *token)) != 0)
518  new_kernel=ParseKernelName(p,exception);
519  else /* otherwise a user defined kernel array */
520  new_kernel=ParseKernelArray(p);
521 
522  /* Error handling -- this is not proper error handling! */
523  if (new_kernel == (KernelInfo *) NULL)
524  {
525  if (kernel != (KernelInfo *) NULL)
526  kernel=DestroyKernelInfo(kernel);
527  return((KernelInfo *) NULL);
528  }
529 
530  /* initialise or append the kernel list */
531  if (kernel == (KernelInfo *) NULL)
532  kernel=new_kernel;
533  else
534  LastKernelInfo(kernel)->next=new_kernel;
535  }
536 
537  /* look for the next kernel in list */
538  p=strchr(p,';');
539  if (p == (char *) NULL)
540  break;
541  p++;
542  }
543  if (kernel_cache != (char *) NULL)
544  kernel_cache=DestroyString(kernel_cache);
545  return(kernel);
546 }
547 ␌
548 /*
549 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
550 % %
551 % %
552 % %
553 % A c q u i r e K e r n e l B u i l t I n %
554 % %
555 % %
556 % %
557 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
558 %
559 % AcquireKernelBuiltIn() returned one of the 'named' built-in types of
560 % kernels used for special purposes such as gaussian blurring, skeleton
561 % pruning, and edge distance determination.
562 %
563 % They take a KernelType, and a set of geometry style arguments, which were
564 % typically decoded from a user supplied string, or from a more complex
565 % Morphology Method that was requested.
566 %
567 % The format of the AcquireKernalBuiltIn method is:
568 %
569 % KernelInfo *AcquireKernelBuiltIn(const KernelInfoType type,
570 % const GeometryInfo args)
571 %
572 % A description of each parameter follows:
573 %
574 % o type: the pre-defined type of kernel wanted
575 %
576 % o args: arguments defining or modifying the kernel
577 %
578 % Convolution Kernels
579 %
580 % Unity
581 % The a No-Op or Scaling single element kernel.
582 %
583 % Gaussian:{radius},{sigma}
584 % Generate a two-dimensional gaussian kernel, as used by -gaussian.
585 % The sigma for the curve is required. The resulting kernel is
586 % normalized,
587 %
588 % If 'sigma' is zero, you get a single pixel on a field of zeros.
589 %
590 % NOTE: that the 'radius' is optional, but if provided can limit (clip)
591 % the final size of the resulting kernel to a square 2*radius+1 in size.
592 % The radius should be at least 2 times that of the sigma value, or
593 % sever clipping and aliasing may result. If not given or set to 0 the
594 % radius will be determined so as to produce the best minimal error
595 % result, which is usally much larger than is normally needed.
596 %
597 % LoG:{radius},{sigma}
598 % "Laplacian of a Gaussian" or "Mexician Hat" Kernel.
599 % The supposed ideal edge detection, zero-summing kernel.
600 %
601 % An alturnative to this kernel is to use a "DoG" with a sigma ratio of
602 % approx 1.6 (according to wikipedia).
603 %
604 % DoG:{radius},{sigma1},{sigma2}
605 % "Difference of Gaussians" Kernel.
606 % As "Gaussian" but with a gaussian produced by 'sigma2' subtracted
607 % from the gaussian produced by 'sigma1'. Typically sigma2 > sigma1.
608 % The result is a zero-summing kernel.
609 %
610 % Blur:{radius},{sigma}[,{angle}]
611 % Generates a 1 dimensional or linear gaussian blur, at the angle given
612 % (current restricted to orthogonal angles). If a 'radius' is given the
613 % kernel is clipped to a width of 2*radius+1. Kernel can be rotated
614 % by a 90 degree angle.
615 %
616 % If 'sigma' is zero, you get a single pixel on a field of zeros.
617 %
618 % Note that two convolutions with two "Blur" kernels perpendicular to
619 % each other, is equivalent to a far larger "Gaussian" kernel with the
620 % same sigma value, However it is much faster to apply. This is how the
621 % "-blur" operator actually works.
622 %
623 % Comet:{width},{sigma},{angle}
624 % Blur in one direction only, much like how a bright object leaves
625 % a comet like trail. The Kernel is actually half a gaussian curve,
626 % Adding two such blurs in opposite directions produces a Blur Kernel.
627 % Angle can be rotated in multiples of 90 degrees.
628 %
629 % Note that the first argument is the width of the kernel and not the
630 % radius of the kernel.
631 %
632 % Binomial:[{radius}]
633 % Generate a discrete kernel using a 2 dimentional Pascel's Triangle
634 % of values. Used for special forma of image filters.
635 %
636 % # Still to be implemented...
637 % #
638 % # Filter2D
639 % # Filter1D
640 % # Set kernel values using a resize filter, and given scale (sigma)
641 % # Cylindrical or Linear. Is this possible with an image?
642 % #
643 %
644 % Named Constant Convolution Kernels
645 %
646 % All these are unscaled, zero-summing kernels by default. As such for
647 % non-HDRI version of ImageMagick some form of normalization, user scaling,
648 % and biasing the results is recommended, to prevent the resulting image
649 % being 'clipped'.
650 %
651 % The 3x3 kernels (most of these) can be circularly rotated in multiples of
652 % 45 degrees to generate the 8 angled varients of each of the kernels.
653 %
654 % Laplacian:{type}
655 % Discrete Lapacian Kernels, (without normalization)
656 % Type 0 : 3x3 with center:8 surounded by -1 (8 neighbourhood)
657 % Type 1 : 3x3 with center:4 edge:-1 corner:0 (4 neighbourhood)
658 % Type 2 : 3x3 with center:4 edge:1 corner:-2
659 % Type 3 : 3x3 with center:4 edge:-2 corner:1
660 % Type 5 : 5x5 laplacian
661 % Type 7 : 7x7 laplacian
662 % Type 15 : 5x5 LoG (sigma approx 1.4)
663 % Type 19 : 9x9 LoG (sigma approx 1.4)
664 %
665 % Sobel:{angle}
666 % Sobel 'Edge' convolution kernel (3x3)
667 % | -1, 0, 1 |
668 % | -2, 0,-2 |
669 % | -1, 0, 1 |
670 %
671 % Roberts:{angle}
672 % Roberts convolution kernel (3x3)
673 % | 0, 0, 0 |
674 % | -1, 1, 0 |
675 % | 0, 0, 0 |
676 %
677 % Prewitt:{angle}
678 % Prewitt Edge convolution kernel (3x3)
679 % | -1, 0, 1 |
680 % | -1, 0, 1 |
681 % | -1, 0, 1 |
682 %
683 % Compass:{angle}
684 % Prewitt's "Compass" convolution kernel (3x3)
685 % | -1, 1, 1 |
686 % | -1,-2, 1 |
687 % | -1, 1, 1 |
688 %
689 % Kirsch:{angle}
690 % Kirsch's "Compass" convolution kernel (3x3)
691 % | -3,-3, 5 |
692 % | -3, 0, 5 |
693 % | -3,-3, 5 |
694 %
695 % FreiChen:{angle}
696 % Frei-Chen Edge Detector is based on a kernel that is similar to
697 % the Sobel Kernel, but is designed to be isotropic. That is it takes
698 % into account the distance of the diagonal in the kernel.
699 %
700 % | 1, 0, -1 |
701 % | sqrt(2), 0, -sqrt(2) |
702 % | 1, 0, -1 |
703 %
704 % FreiChen:{type},{angle}
705 %
706 % Frei-Chen Pre-weighted kernels...
707 %
708 % Type 0: default un-nomalized version shown above.
709 %
710 % Type 1: Orthogonal Kernel (same as type 11 below)
711 % | 1, 0, -1 |
712 % | sqrt(2), 0, -sqrt(2) | / 2*sqrt(2)
713 % | 1, 0, -1 |
714 %
715 % Type 2: Diagonal form of Kernel...
716 % | 1, sqrt(2), 0 |
717 % | sqrt(2), 0, -sqrt(2) | / 2*sqrt(2)
718 % | 0, -sqrt(2) -1 |
719 %
720 % However this kernel is als at the heart of the FreiChen Edge Detection
721 % Process which uses a set of 9 specially weighted kernel. These 9
722 % kernels not be normalized, but directly applied to the image. The
723 % results is then added together, to produce the intensity of an edge in
724 % a specific direction. The square root of the pixel value can then be
725 % taken as the cosine of the edge, and at least 2 such runs at 90 degrees
726 % from each other, both the direction and the strength of the edge can be
727 % determined.
728 %
729 % Type 10: All 9 of the following pre-weighted kernels...
730 %
731 % Type 11: | 1, 0, -1 |
732 % | sqrt(2), 0, -sqrt(2) | / 2*sqrt(2)
733 % | 1, 0, -1 |
734 %
735 % Type 12: | 1, sqrt(2), 1 |
736 % | 0, 0, 0 | / 2*sqrt(2)
737 % | 1, sqrt(2), 1 |
738 %
739 % Type 13: | sqrt(2), -1, 0 |
740 % | -1, 0, 1 | / 2*sqrt(2)
741 % | 0, 1, -sqrt(2) |
742 %
743 % Type 14: | 0, 1, -sqrt(2) |
744 % | -1, 0, 1 | / 2*sqrt(2)
745 % | sqrt(2), -1, 0 |
746 %
747 % Type 15: | 0, -1, 0 |
748 % | 1, 0, 1 | / 2
749 % | 0, -1, 0 |
750 %
751 % Type 16: | 1, 0, -1 |
752 % | 0, 0, 0 | / 2
753 % | -1, 0, 1 |
754 %
755 % Type 17: | 1, -2, 1 |
756 % | -2, 4, -2 | / 6
757 % | -1, -2, 1 |
758 %
759 % Type 18: | -2, 1, -2 |
760 % | 1, 4, 1 | / 6
761 % | -2, 1, -2 |
762 %
763 % Type 19: | 1, 1, 1 |
764 % | 1, 1, 1 | / 3
765 % | 1, 1, 1 |
766 %
767 % The first 4 are for edge detection, the next 4 are for line detection
768 % and the last is to add a average component to the results.
769 %
770 % Using a special type of '-1' will return all 9 pre-weighted kernels
771 % as a multi-kernel list, so that you can use them directly (without
772 % normalization) with the special "-set option:morphology:compose Plus"
773 % setting to apply the full FreiChen Edge Detection Technique.
774 %
775 % If 'type' is large it will be taken to be an actual rotation angle for
776 % the default FreiChen (type 0) kernel. As such FreiChen:45 will look
777 % like a Sobel:45 but with 'sqrt(2)' instead of '2' values.
778 %
779 % WARNING: The above was layed out as per
780 % http://www.math.tau.ac.il/~turkel/notes/edge_detectors.pdf
781 % But rotated 90 degrees so direction is from left rather than the top.
782 % I have yet to find any secondary confirmation of the above. The only
783 % other source found was actual source code at
784 % http://ltswww.epfl.ch/~courstiv/exos_labos/sol3.pdf
785 % Neigher paper defineds the kernels in a way that looks locical or
786 % correct when taken as a whole.
787 %
788 % Boolean Kernels
789 %
790 % Diamond:[{radius}[,{scale}]]
791 % Generate a diamond shaped kernel with given radius to the points.
792 % Kernel size will again be radius*2+1 square and defaults to radius 1,
793 % generating a 3x3 kernel that is slightly larger than a square.
794 %
795 % Square:[{radius}[,{scale}]]
796 % Generate a square shaped kernel of size radius*2+1, and defaulting
797 % to a 3x3 (radius 1).
798 %
799 % Octagon:[{radius}[,{scale}]]
800 % Generate octagonal shaped kernel of given radius and constant scale.
801 % Default radius is 3 producing a 7x7 kernel. A radius of 1 will result
802 % in "Diamond" kernel.
803 %
804 % Disk:[{radius}[,{scale}]]
805 % Generate a binary disk, thresholded at the radius given, the radius
806 % may be a float-point value. Final Kernel size is floor(radius)*2+1
807 % square. A radius of 5.3 is the default.
808 %
809 % NOTE: That a low radii Disk kernels produce the same results as
810 % many of the previously defined kernels, but differ greatly at larger
811 % radii. Here is a table of equivalences...
812 % "Disk:1" => "Diamond", "Octagon:1", or "Cross:1"
813 % "Disk:1.5" => "Square"
814 % "Disk:2" => "Diamond:2"
815 % "Disk:2.5" => "Octagon"
816 % "Disk:2.9" => "Square:2"
817 % "Disk:3.5" => "Octagon:3"
818 % "Disk:4.5" => "Octagon:4"
819 % "Disk:5.4" => "Octagon:5"
820 % "Disk:6.4" => "Octagon:6"
821 % All other Disk shapes are unique to this kernel, but because a "Disk"
822 % is more circular when using a larger radius, using a larger radius is
823 % preferred over iterating the morphological operation.
824 %
825 % Rectangle:{geometry}
826 % Simply generate a rectangle of 1's with the size given. You can also
827 % specify the location of the 'control point', otherwise the closest
828 % pixel to the center of the rectangle is selected.
829 %
830 % Properly centered and odd sized rectangles work the best.
831 %
832 % Symbol Dilation Kernels
833 %
834 % These kernel is not a good general morphological kernel, but is used
835 % more for highlighting and marking any single pixels in an image using,
836 % a "Dilate" method as appropriate.
837 %
838 % For the same reasons iterating these kernels does not produce the
839 % same result as using a larger radius for the symbol.
840 %
841 % Plus:[{radius}[,{scale}]]
842 % Cross:[{radius}[,{scale}]]
843 % Generate a kernel in the shape of a 'plus' or a 'cross' with
844 % a each arm the length of the given radius (default 2).
845 %
846 % NOTE: "plus:1" is equivalent to a "Diamond" kernel.
847 %
848 % Ring:{radius1},{radius2}[,{scale}]
849 % A ring of the values given that falls between the two radii.
850 % Defaults to a ring of approximataly 3 radius in a 7x7 kernel.
851 % This is the 'edge' pixels of the default "Disk" kernel,
852 % More specifically, "Ring" -> "Ring:2.5,3.5,1.0"
853 %
854 % Hit and Miss Kernels
855 %
856 % Peak:radius1,radius2
857 % Find any peak larger than the pixels the fall between the two radii.
858 % The default ring of pixels is as per "Ring".
859 % Edges
860 % Find flat orthogonal edges of a binary shape
861 % Corners
862 % Find 90 degree corners of a binary shape
863 % Diagonals:type
864 % A special kernel to thin the 'outside' of diagonals
865 % LineEnds:type
866 % Find end points of lines (for pruning a skeletion)
867 % Two types of lines ends (default to both) can be searched for
868 % Type 0: All line ends
869 % Type 1: single kernel for 4-conneected line ends
870 % Type 2: single kernel for simple line ends
871 % LineJunctions
872 % Find three line junctions (within a skeletion)
873 % Type 0: all line junctions
874 % Type 1: Y Junction kernel
875 % Type 2: Diagonal T Junction kernel
876 % Type 3: Orthogonal T Junction kernel
877 % Type 4: Diagonal X Junction kernel
878 % Type 5: Orthogonal + Junction kernel
879 % Ridges:type
880 % Find single pixel ridges or thin lines
881 % Type 1: Fine single pixel thick lines and ridges
882 % Type 2: Find two pixel thick lines and ridges
883 % ConvexHull
884 % Octagonal Thickening Kernel, to generate convex hulls of 45 degrees
885 % Skeleton:type
886 % Traditional skeleton generating kernels.
887 % Type 1: Tradional Skeleton kernel (4 connected skeleton)
888 % Type 2: HIPR2 Skeleton kernel (8 connected skeleton)
889 % Type 3: Thinning skeleton based on a ressearch paper by
890 % Dan S. Bloomberg (Default Type)
891 % ThinSE:type
892 % A huge variety of Thinning Kernels designed to preserve conectivity.
893 % many other kernel sets use these kernels as source definitions.
894 % Type numbers are 41-49, 81-89, 481, and 482 which are based on
895 % the super and sub notations used in the source research paper.
896 %
897 % Distance Measuring Kernels
898 %
899 % Different types of distance measuring methods, which are used with the
900 % a 'Distance' morphology method for generating a gradient based on
901 % distance from an edge of a binary shape, though there is a technique
902 % for handling a anti-aliased shape.
903 %
904 % See the 'Distance' Morphological Method, for information of how it is
905 % applied.
906 %
907 % Chebyshev:[{radius}][x{scale}[%!]]
908 % Chebyshev Distance (also known as Tchebychev or Chessboard distance)
909 % is a value of one to any neighbour, orthogonal or diagonal. One why
910 % of thinking of it is the number of squares a 'King' or 'Queen' in
911 % chess needs to traverse reach any other position on a chess board.
912 % It results in a 'square' like distance function, but one where
913 % diagonals are given a value that is closer than expected.
914 %
915 % Manhattan:[{radius}][x{scale}[%!]]
916 % Manhattan Distance (also known as Rectilinear, City Block, or the Taxi
917 % Cab distance metric), it is the distance needed when you can only
918 % travel in horizontal or vertical directions only. It is the
919 % distance a 'Rook' in chess would have to travel, and results in a
920 % diamond like distances, where diagonals are further than expected.
921 %
922 % Octagonal:[{radius}][x{scale}[%!]]
923 % An interleving of Manhatten and Chebyshev metrics producing an
924 % increasing octagonally shaped distance. Distances matches those of
925 % the "Octagon" shaped kernel of the same radius. The minimum radius
926 % and default is 2, producing a 5x5 kernel.
927 %
928 % Euclidean:[{radius}][x{scale}[%!]]
929 % Euclidean distance is the 'direct' or 'as the crow flys' distance.
930 % However by default the kernel size only has a radius of 1, which
931 % limits the distance to 'Knight' like moves, with only orthogonal and
932 % diagonal measurements being correct. As such for the default kernel
933 % you will get octagonal like distance function.
934 %
935 % However using a larger radius such as "Euclidean:4" you will get a
936 % much smoother distance gradient from the edge of the shape. Especially
937 % if the image is pre-processed to include any anti-aliasing pixels.
938 % Of course a larger kernel is slower to use, and not always needed.
939 %
940 % The first three Distance Measuring Kernels will only generate distances
941 % of exact multiples of {scale} in binary images. As such you can use a
942 % scale of 1 without loosing any information. However you also need some
943 % scaling when handling non-binary anti-aliased shapes.
944 %
945 % The "Euclidean" Distance Kernel however does generate a non-integer
946 % fractional results, and as such scaling is vital even for binary shapes.
947 %
948 */
949 
950 MagickExport KernelInfo *AcquireKernelBuiltIn(const KernelInfoType type,
951  const GeometryInfo *args,ExceptionInfo *exception)
952 {
953  KernelInfo
954  *kernel;
955 
956  ssize_t
957  i;
958 
959  ssize_t
960  u,
961  v;
962 
963  double
964  nan = sqrt((double)-1.0); /* Special Value : Not A Number */
965 
966  /* Generate a new empty kernel if needed */
967  kernel=(KernelInfo *) NULL;
968  switch(type) {
969  case UndefinedKernel: /* These should not call this function */
970  case UserDefinedKernel:
971  ThrowMagickException(exception,GetMagickModule(),OptionWarning,
972  "InvalidOption","`%s'","Should not call this function");
973  return((KernelInfo *) NULL);
974  case LaplacianKernel: /* Named Descrete Convolution Kernels */
975  case SobelKernel: /* these are defined using other kernels */
976  case RobertsKernel:
977  case PrewittKernel:
978  case CompassKernel:
979  case KirschKernel:
980  case FreiChenKernel:
981  case EdgesKernel: /* Hit and Miss kernels */
982  case CornersKernel:
983  case DiagonalsKernel:
984  case LineEndsKernel:
985  case LineJunctionsKernel:
986  case RidgesKernel:
987  case ConvexHullKernel:
988  case SkeletonKernel:
989  case ThinSEKernel:
990  break; /* A pre-generated kernel is not needed */
991 #if 0
992  /* set to 1 to do a compile-time check that we haven't missed anything */
993  case UnityKernel:
994  case GaussianKernel:
995  case DoGKernel:
996  case LoGKernel:
997  case BlurKernel:
998  case CometKernel:
999  case BinomialKernel:
1000  case DiamondKernel:
1001  case SquareKernel:
1002  case RectangleKernel:
1003  case OctagonKernel:
1004  case DiskKernel:
1005  case PlusKernel:
1006  case CrossKernel:
1007  case RingKernel:
1008  case PeaksKernel:
1009  case ChebyshevKernel:
1010  case ManhattanKernel:
1011  case OctangonalKernel:
1012  case EuclideanKernel:
1013 #else
1014  default:
1015 #endif
1016  /* Generate the base Kernel Structure */
1017  kernel=(KernelInfo *) AcquireMagickMemory(sizeof(*kernel));
1018  if (kernel == (KernelInfo *) NULL)
1019  return(kernel);
1020  (void) memset(kernel,0,sizeof(*kernel));
1021  kernel->minimum = kernel->maximum = kernel->angle = 0.0;
1022  kernel->negative_range = kernel->positive_range = 0.0;
1023  kernel->type = type;
1024  kernel->next = (KernelInfo *) NULL;
1025  kernel->signature=MagickCoreSignature;
1026  break;
1027  }
1028 
1029  switch(type) {
1030  /*
1031  Convolution Kernels
1032  */
1033  case UnityKernel:
1034  {
1035  kernel->height = kernel->width = (size_t) 1;
1036  kernel->x = kernel->y = (ssize_t) 0;
1037  kernel->values=(MagickRealType *) MagickAssumeAligned(
1038  AcquireAlignedMemory(1,sizeof(*kernel->values)));
1039  if (kernel->values == (MagickRealType *) NULL)
1040  return(DestroyKernelInfo(kernel));
1041  kernel->maximum = kernel->values[0] = args->rho;
1042  break;
1043  }
1044  break;
1045  case GaussianKernel:
1046  case DoGKernel:
1047  case LoGKernel:
1048  { double
1049  sigma = fabs(args->sigma),
1050  sigma2 = fabs(args->xi),
1051  A, B, R;
1052 
1053  if ( args->rho >= 1.0 )
1054  kernel->width = (size_t)args->rho*2+1;
1055  else if ( (type != DoGKernel) || (sigma >= sigma2) )
1056  kernel->width = GetOptimalKernelWidth2D(args->rho,sigma);
1057  else
1058  kernel->width = GetOptimalKernelWidth2D(args->rho,sigma2);
1059  kernel->height = kernel->width;
1060  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1061  kernel->values=(MagickRealType *) MagickAssumeAligned(
1062  AcquireAlignedMemory(kernel->width,kernel->height*
1063  sizeof(*kernel->values)));
1064  if (kernel->values == (MagickRealType *) NULL)
1065  return(DestroyKernelInfo(kernel));
1066 
1067  /* WARNING: The following generates a 'sampled gaussian' kernel.
1068  * What we really want is a 'discrete gaussian' kernel.
1069  *
1070  * How to do this is I don't know, but appears to be basied on the
1071  * Error Function 'erf()' (intergral of a gaussian)
1072  */
1073 
1074  if ( type == GaussianKernel || type == DoGKernel )
1075  { /* Calculate a Gaussian, OR positive half of a DoG */
1076  if ( sigma > MagickEpsilon )
1077  { A = 1.0/(2.0*sigma*sigma); /* simplify loop expressions */
1078  B = (double) (1.0/(Magick2PI*sigma*sigma));
1079  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1080  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1081  kernel->values[i] = exp(-((double)(u*u+v*v))*A)*B;
1082  }
1083  else /* limiting case - a unity (normalized Dirac) kernel */
1084  { (void) memset(kernel->values,0, (size_t)
1085  kernel->width*kernel->height*sizeof(*kernel->values));
1086  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1087  }
1088  }
1089 
1090  if ( type == DoGKernel )
1091  { /* Subtract a Negative Gaussian for "Difference of Gaussian" */
1092  if ( sigma2 > MagickEpsilon )
1093  { sigma = sigma2; /* simplify loop expressions */
1094  A = 1.0/(2.0*sigma*sigma);
1095  B = (double) (1.0/(Magick2PI*sigma*sigma));
1096  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1097  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1098  kernel->values[i] -= exp(-((double)(u*u+v*v))*A)*B;
1099  }
1100  else /* limiting case - a unity (normalized Dirac) kernel */
1101  kernel->values[kernel->x+kernel->y*kernel->width] -= 1.0;
1102  }
1103 
1104  if ( type == LoGKernel )
1105  { /* Calculate a Laplacian of a Gaussian - Or Mexician Hat */
1106  if ( sigma > MagickEpsilon )
1107  { A = 1.0/(2.0*sigma*sigma); /* simplify loop expressions */
1108  B = (double) (1.0/(MagickPI*sigma*sigma*sigma*sigma));
1109  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1110  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1111  { R = ((double)(u*u+v*v))*A;
1112  kernel->values[i] = (1-R)*exp(-R)*B;
1113  }
1114  }
1115  else /* special case - generate a unity kernel */
1116  { (void) memset(kernel->values,0, (size_t)
1117  kernel->width*kernel->height*sizeof(*kernel->values));
1118  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1119  }
1120  }
1121 
1122  /* Note the above kernels may have been 'clipped' by a user defined
1123  ** radius, producing a smaller (darker) kernel. Also for very small
1124  ** sigma's (> 0.1) the central value becomes larger than one, and thus
1125  ** producing a very bright kernel.
1126  **
1127  ** Normalization will still be needed.
1128  */
1129 
1130  /* Normalize the 2D Gaussian Kernel
1131  **
1132  ** NB: a CorrelateNormalize performs a normal Normalize if
1133  ** there are no negative values.
1134  */
1135  CalcKernelMetaData(kernel); /* the other kernel meta-data */
1136  ScaleKernelInfo(kernel, 1.0, CorrelateNormalizeValue);
1137 
1138  break;
1139  }
1140  case BlurKernel:
1141  { double
1142  sigma = fabs(args->sigma),
1143  alpha, beta;
1144 
1145  if ( args->rho >= 1.0 )
1146  kernel->width = (size_t)args->rho*2+1;
1147  else
1148  kernel->width = GetOptimalKernelWidth1D(args->rho,sigma);
1149  kernel->height = 1;
1150  kernel->x = (ssize_t) (kernel->width-1)/2;
1151  kernel->y = 0;
1152  kernel->negative_range = kernel->positive_range = 0.0;
1153  kernel->values=(MagickRealType *) MagickAssumeAligned(
1154  AcquireAlignedMemory(kernel->width,kernel->height*
1155  sizeof(*kernel->values)));
1156  if (kernel->values == (MagickRealType *) NULL)
1157  return(DestroyKernelInfo(kernel));
1158 
1159 #if 1
1160 #define KernelRank 3
1161  /* Formula derived from GetBlurKernel() in "effect.c" (plus bug fix).
1162  ** It generates a gaussian 3 times the width, and compresses it into
1163  ** the expected range. This produces a closer normalization of the
1164  ** resulting kernel, especially for very low sigma values.
1165  ** As such while wierd it is prefered.
1166  **
1167  ** I am told this method originally came from Photoshop.
1168  **
1169  ** A properly normalized curve is generated (apart from edge clipping)
1170  ** even though we later normalize the result (for edge clipping)
1171  ** to allow the correct generation of a "Difference of Blurs".
1172  */
1173 
1174  /* initialize */
1175  v = (ssize_t) (kernel->width*KernelRank-1)/2; /* start/end points to fit range */
1176  (void) memset(kernel->values,0, (size_t)
1177  kernel->width*kernel->height*sizeof(*kernel->values));
1178  /* Calculate a Positive 1D Gaussian */
1179  if ( sigma > MagickEpsilon )
1180  { sigma *= KernelRank; /* simplify loop expressions */
1181  alpha = 1.0/(2.0*sigma*sigma);
1182  beta= (double) (1.0/(MagickSQ2PI*sigma ));
1183  for ( u=-v; u <= v; u++) {
1184  kernel->values[(u+v)/KernelRank] +=
1185  exp(-((double)(u*u))*alpha)*beta;
1186  }
1187  }
1188  else /* special case - generate a unity kernel */
1189  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1190 #else
1191  /* Direct calculation without curve averaging
1192  This is equivelent to a KernelRank of 1 */
1193 
1194  /* Calculate a Positive Gaussian */
1195  if ( sigma > MagickEpsilon )
1196  { alpha = 1.0/(2.0*sigma*sigma); /* simplify loop expressions */
1197  beta = 1.0/(MagickSQ2PI*sigma);
1198  for ( i=0, u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1199  kernel->values[i] = exp(-((double)(u*u))*alpha)*beta;
1200  }
1201  else /* special case - generate a unity kernel */
1202  { (void) memset(kernel->values,0, (size_t)
1203  kernel->width*kernel->height*sizeof(*kernel->values));
1204  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1205  }
1206 #endif
1207  /* Note the above kernel may have been 'clipped' by a user defined
1208  ** radius, producing a smaller (darker) kernel. Also for very small
1209  ** sigma's (> 0.1) the central value becomes larger than one, as a
1210  ** result of not generating a actual 'discrete' kernel, and thus
1211  ** producing a very bright 'impulse'.
1212  **
1213  ** Becuase of these two factors Normalization is required!
1214  */
1215 
1216  /* Normalize the 1D Gaussian Kernel
1217  **
1218  ** NB: a CorrelateNormalize performs a normal Normalize if
1219  ** there are no negative values.
1220  */
1221  CalcKernelMetaData(kernel); /* the other kernel meta-data */
1222  ScaleKernelInfo(kernel, 1.0, CorrelateNormalizeValue);
1223 
1224  /* rotate the 1D kernel by given angle */
1225  RotateKernelInfo(kernel, args->xi );
1226  break;
1227  }
1228  case CometKernel:
1229  { double
1230  sigma = fabs(args->sigma),
1231  A;
1232 
1233  if ( args->rho < 1.0 )
1234  kernel->width = (GetOptimalKernelWidth1D(args->rho,sigma)-1)/2+1;
1235  else
1236  kernel->width = (size_t)args->rho;
1237  kernel->x = kernel->y = 0;
1238  kernel->height = 1;
1239  kernel->negative_range = kernel->positive_range = 0.0;
1240  kernel->values=(MagickRealType *) MagickAssumeAligned(
1241  AcquireAlignedMemory(kernel->width,kernel->height*
1242  sizeof(*kernel->values)));
1243  if (kernel->values == (MagickRealType *) NULL)
1244  return(DestroyKernelInfo(kernel));
1245 
1246  /* A comet blur is half a 1D gaussian curve, so that the object is
1247  ** blurred in one direction only. This may not be quite the right
1248  ** curve to use so may change in the future. The function must be
1249  ** normalised after generation, which also resolves any clipping.
1250  **
1251  ** As we are normalizing and not subtracting gaussians,
1252  ** there is no need for a divisor in the gaussian formula
1253  **
1254  ** It is less comples
1255  */
1256  if ( sigma > MagickEpsilon )
1257  {
1258 #if 1
1259 #define KernelRank 3
1260  v = (ssize_t) kernel->width*KernelRank; /* start/end points */
1261  (void) memset(kernel->values,0, (size_t)
1262  kernel->width*sizeof(*kernel->values));
1263  sigma *= KernelRank; /* simplify the loop expression */
1264  A = 1.0/(2.0*sigma*sigma);
1265  /* B = 1.0/(MagickSQ2PI*sigma); */
1266  for ( u=0; u < v; u++) {
1267  kernel->values[u/KernelRank] +=
1268  exp(-((double)(u*u))*A);
1269  /* exp(-((double)(i*i))/2.0*sigma*sigma)/(MagickSQ2PI*sigma); */
1270  }
1271  for (i=0; i < (ssize_t) kernel->width; i++)
1272  kernel->positive_range += kernel->values[i];
1273 #else
1274  A = 1.0/(2.0*sigma*sigma); /* simplify the loop expression */
1275  /* B = 1.0/(MagickSQ2PI*sigma); */
1276  for ( i=0; i < (ssize_t) kernel->width; i++)
1277  kernel->positive_range +=
1278  kernel->values[i] = exp(-((double)(i*i))*A);
1279  /* exp(-((double)(i*i))/2.0*sigma*sigma)/(MagickSQ2PI*sigma); */
1280 #endif
1281  }
1282  else /* special case - generate a unity kernel */
1283  { (void) memset(kernel->values,0, (size_t)
1284  kernel->width*kernel->height*sizeof(*kernel->values));
1285  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1286  kernel->positive_range = 1.0;
1287  }
1288 
1289  kernel->minimum = 0.0;
1290  kernel->maximum = kernel->values[0];
1291  kernel->negative_range = 0.0;
1292 
1293  ScaleKernelInfo(kernel, 1.0, NormalizeValue); /* Normalize */
1294  RotateKernelInfo(kernel, args->xi); /* Rotate by angle */
1295  break;
1296  }
1297  case BinomialKernel:
1298  {
1299  size_t
1300  order_f;
1301 
1302  if (args->rho < 1.0)
1303  kernel->width = kernel->height = 3; /* default radius = 1 */
1304  else
1305  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
1306  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1307 
1308  order_f = fact(kernel->width-1);
1309 
1310  kernel->values=(MagickRealType *) MagickAssumeAligned(
1311  AcquireAlignedMemory(kernel->width,kernel->height*
1312  sizeof(*kernel->values)));
1313  if (kernel->values == (MagickRealType *) NULL)
1314  return(DestroyKernelInfo(kernel));
1315 
1316  /* set all kernel values within diamond area to scale given */
1317  for ( i=0, v=0; v < (ssize_t)kernel->height; v++)
1318  { size_t
1319  alpha = order_f / ( fact((size_t) v) * fact(kernel->height-v-1) );
1320  for ( u=0; u < (ssize_t)kernel->width; u++, i++)
1321  kernel->positive_range += kernel->values[i] = (double)
1322  (alpha * order_f / ( fact((size_t) u) * fact(kernel->height-u-1) ));
1323  }
1324  kernel->minimum = 1.0;
1325  kernel->maximum = kernel->values[kernel->x+kernel->y*kernel->width];
1326  kernel->negative_range = 0.0;
1327  break;
1328  }
1329 
1330  /*
1331  Convolution Kernels - Well Known Named Constant Kernels
1332  */
1333  case LaplacianKernel:
1334  { switch ( (int) args->rho ) {
1335  case 0:
1336  default: /* laplacian square filter -- default */
1337  kernel=ParseKernelArray("3: -1,-1,-1 -1,8,-1 -1,-1,-1");
1338  break;
1339  case 1: /* laplacian diamond filter */
1340  kernel=ParseKernelArray("3: 0,-1,0 -1,4,-1 0,-1,0");
1341  break;
1342  case 2:
1343  kernel=ParseKernelArray("3: -2,1,-2 1,4,1 -2,1,-2");
1344  break;
1345  case 3:
1346  kernel=ParseKernelArray("3: 1,-2,1 -2,4,-2 1,-2,1");
1347  break;
1348  case 5: /* a 5x5 laplacian */
1349  kernel=ParseKernelArray(
1350  "5: -4,-1,0,-1,-4 -1,2,3,2,-1 0,3,4,3,0 -1,2,3,2,-1 -4,-1,0,-1,-4");
1351  break;
1352  case 7: /* a 7x7 laplacian */
1353  kernel=ParseKernelArray(
1354  "7:-10,-5,-2,-1,-2,-5,-10 -5,0,3,4,3,0,-5 -2,3,6,7,6,3,-2 -1,4,7,8,7,4,-1 -2,3,6,7,6,3,-2 -5,0,3,4,3,0,-5 -10,-5,-2,-1,-2,-5,-10" );
1355  break;
1356  case 15: /* a 5x5 LoG (sigma approx 1.4) */
1357  kernel=ParseKernelArray(
1358  "5: 0,0,-1,0,0 0,-1,-2,-1,0 -1,-2,16,-2,-1 0,-1,-2,-1,0 0,0,-1,0,0");
1359  break;
1360  case 19: /* a 9x9 LoG (sigma approx 1.4) */
1361  /* http://www.cscjournals.org/csc/manuscript/Journals/IJIP/volume3/Issue1/IJIP-15.pdf */
1362  kernel=ParseKernelArray(
1363  "9: 0,-1,-1,-2,-2,-2,-1,-1,0 -1,-2,-4,-5,-5,-5,-4,-2,-1 -1,-4,-5,-3,-0,-3,-5,-4,-1 -2,-5,-3,12,24,12,-3,-5,-2 -2,-5,-0,24,40,24,-0,-5,-2 -2,-5,-3,12,24,12,-3,-5,-2 -1,-4,-5,-3,-0,-3,-5,-4,-1 -1,-2,-4,-5,-5,-5,-4,-2,-1 0,-1,-1,-2,-2,-2,-1,-1,0");
1364  break;
1365  }
1366  if (kernel == (KernelInfo *) NULL)
1367  return(kernel);
1368  kernel->type = type;
1369  break;
1370  }
1371  case SobelKernel:
1372  { /* Simple Sobel Kernel */
1373  kernel=ParseKernelArray("3: 1,0,-1 2,0,-2 1,0,-1");
1374  if (kernel == (KernelInfo *) NULL)
1375  return(kernel);
1376  kernel->type = type;
1377  RotateKernelInfo(kernel, args->rho);
1378  break;
1379  }
1380  case RobertsKernel:
1381  {
1382  kernel=ParseKernelArray("3: 0,0,0 1,-1,0 0,0,0");
1383  if (kernel == (KernelInfo *) NULL)
1384  return(kernel);
1385  kernel->type = type;
1386  RotateKernelInfo(kernel, args->rho);
1387  break;
1388  }
1389  case PrewittKernel:
1390  {
1391  kernel=ParseKernelArray("3: 1,0,-1 1,0,-1 1,0,-1");
1392  if (kernel == (KernelInfo *) NULL)
1393  return(kernel);
1394  kernel->type = type;
1395  RotateKernelInfo(kernel, args->rho);
1396  break;
1397  }
1398  case CompassKernel:
1399  {
1400  kernel=ParseKernelArray("3: 1,1,-1 1,-2,-1 1,1,-1");
1401  if (kernel == (KernelInfo *) NULL)
1402  return(kernel);
1403  kernel->type = type;
1404  RotateKernelInfo(kernel, args->rho);
1405  break;
1406  }
1407  case KirschKernel:
1408  {
1409  kernel=ParseKernelArray("3: 5,-3,-3 5,0,-3 5,-3,-3");
1410  if (kernel == (KernelInfo *) NULL)
1411  return(kernel);
1412  kernel->type = type;
1413  RotateKernelInfo(kernel, args->rho);
1414  break;
1415  }
1416  case FreiChenKernel:
1417  /* Direction is set to be left to right positive */
1418  /* http://www.math.tau.ac.il/~turkel/notes/edge_detectors.pdf -- RIGHT? */
1419  /* http://ltswww.epfl.ch/~courstiv/exos_labos/sol3.pdf -- WRONG? */
1420  { switch ( (int) args->rho ) {
1421  default:
1422  case 0:
1423  kernel=ParseKernelArray("3: 1,0,-1 2,0,-2 1,0,-1");
1424  if (kernel == (KernelInfo *) NULL)
1425  return(kernel);
1426  kernel->type = type;
1427  kernel->values[3] = +(MagickRealType) MagickSQ2;
1428  kernel->values[5] = -(MagickRealType) MagickSQ2;
1429  CalcKernelMetaData(kernel); /* recalculate meta-data */
1430  break;
1431  case 2:
1432  kernel=ParseKernelArray("3: 1,2,0 2,0,-2 0,-2,-1");
1433  if (kernel == (KernelInfo *) NULL)
1434  return(kernel);
1435  kernel->type = type;
1436  kernel->values[1] = kernel->values[3]= +(MagickRealType) MagickSQ2;
1437  kernel->values[5] = kernel->values[7]= -(MagickRealType) MagickSQ2;
1438  CalcKernelMetaData(kernel); /* recalculate meta-data */
1439  ScaleKernelInfo(kernel, (double) (1.0/2.0*MagickSQ2), NoValue);
1440  break;
1441  case 10:
1442  {
1443  kernel=AcquireKernelInfo("FreiChen:11;FreiChen:12;FreiChen:13;FreiChen:14;FreiChen:15;FreiChen:16;FreiChen:17;FreiChen:18;FreiChen:19",exception);
1444  if (kernel == (KernelInfo *) NULL)
1445  return(kernel);
1446  break;
1447  }
1448  case 1:
1449  case 11:
1450  kernel=ParseKernelArray("3: 1,0,-1 2,0,-2 1,0,-1");
1451  if (kernel == (KernelInfo *) NULL)
1452  return(kernel);
1453  kernel->type = type;
1454  kernel->values[3] = +(MagickRealType) MagickSQ2;
1455  kernel->values[5] = -(MagickRealType) MagickSQ2;
1456  CalcKernelMetaData(kernel); /* recalculate meta-data */
1457  ScaleKernelInfo(kernel, (double) (1.0/2.0*MagickSQ2), NoValue);
1458  break;
1459  case 12:
1460  kernel=ParseKernelArray("3: 1,2,1 0,0,0 1,2,1");
1461  if (kernel == (KernelInfo *) NULL)
1462  return(kernel);
1463  kernel->type = type;
1464  kernel->values[1] = +(MagickRealType) MagickSQ2;
1465  kernel->values[7] = +(MagickRealType) MagickSQ2;
1466  CalcKernelMetaData(kernel);
1467  ScaleKernelInfo(kernel, (double) (1.0/2.0*MagickSQ2), NoValue);
1468  break;
1469  case 13:
1470  kernel=ParseKernelArray("3: 2,-1,0 -1,0,1 0,1,-2");
1471  if (kernel == (KernelInfo *) NULL)
1472  return(kernel);
1473  kernel->type = type;
1474  kernel->values[0] = +(MagickRealType) MagickSQ2;
1475  kernel->values[8] = -(MagickRealType) MagickSQ2;
1476  CalcKernelMetaData(kernel);
1477  ScaleKernelInfo(kernel, (double) (1.0/2.0*MagickSQ2), NoValue);
1478  break;
1479  case 14:
1480  kernel=ParseKernelArray("3: 0,1,-2 -1,0,1 2,-1,0");
1481  if (kernel == (KernelInfo *) NULL)
1482  return(kernel);
1483  kernel->type = type;
1484  kernel->values[2] = -(MagickRealType) MagickSQ2;
1485  kernel->values[6] = +(MagickRealType) MagickSQ2;
1486  CalcKernelMetaData(kernel);
1487  ScaleKernelInfo(kernel, (double) (1.0/2.0*MagickSQ2), NoValue);
1488  break;
1489  case 15:
1490  kernel=ParseKernelArray("3: 0,-1,0 1,0,1 0,-1,0");
1491  if (kernel == (KernelInfo *) NULL)
1492  return(kernel);
1493  kernel->type = type;
1494  ScaleKernelInfo(kernel, 1.0/2.0, NoValue);
1495  break;
1496  case 16:
1497  kernel=ParseKernelArray("3: 1,0,-1 0,0,0 -1,0,1");
1498  if (kernel == (KernelInfo *) NULL)
1499  return(kernel);
1500  kernel->type = type;
1501  ScaleKernelInfo(kernel, 1.0/2.0, NoValue);
1502  break;
1503  case 17:
1504  kernel=ParseKernelArray("3: 1,-2,1 -2,4,-2 -1,-2,1");
1505  if (kernel == (KernelInfo *) NULL)
1506  return(kernel);
1507  kernel->type = type;
1508  ScaleKernelInfo(kernel, 1.0/6.0, NoValue);
1509  break;
1510  case 18:
1511  kernel=ParseKernelArray("3: -2,1,-2 1,4,1 -2,1,-2");
1512  if (kernel == (KernelInfo *) NULL)
1513  return(kernel);
1514  kernel->type = type;
1515  ScaleKernelInfo(kernel, 1.0/6.0, NoValue);
1516  break;
1517  case 19:
1518  kernel=ParseKernelArray("3: 1,1,1 1,1,1 1,1,1");
1519  if (kernel == (KernelInfo *) NULL)
1520  return(kernel);
1521  kernel->type = type;
1522  ScaleKernelInfo(kernel, 1.0/3.0, NoValue);
1523  break;
1524  }
1525  if ( fabs(args->sigma) >= MagickEpsilon )
1526  /* Rotate by correctly supplied 'angle' */
1527  RotateKernelInfo(kernel, args->sigma);
1528  else if ( args->rho > 30.0 || args->rho < -30.0 )
1529  /* Rotate by out of bounds 'type' */
1530  RotateKernelInfo(kernel, args->rho);
1531  break;
1532  }
1533 
1534  /*
1535  Boolean or Shaped Kernels
1536  */
1537  case DiamondKernel:
1538  {
1539  if (args->rho < 1.0)
1540  kernel->width = kernel->height = 3; /* default radius = 1 */
1541  else
1542  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
1543  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1544 
1545  kernel->values=(MagickRealType *) MagickAssumeAligned(
1546  AcquireAlignedMemory(kernel->width,kernel->height*
1547  sizeof(*kernel->values)));
1548  if (kernel->values == (MagickRealType *) NULL)
1549  return(DestroyKernelInfo(kernel));
1550 
1551  /* set all kernel values within diamond area to scale given */
1552  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1553  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1554  if ( (labs((long) u)+labs((long) v)) <= (long) kernel->x)
1555  kernel->positive_range += kernel->values[i] = args->sigma;
1556  else
1557  kernel->values[i] = nan;
1558  kernel->minimum = kernel->maximum = args->sigma; /* a flat shape */
1559  break;
1560  }
1561  case SquareKernel:
1562  case RectangleKernel:
1563  { double
1564  scale;
1565  if ( type == SquareKernel )
1566  {
1567  if (args->rho < 1.0)
1568  kernel->width = kernel->height = 3; /* default radius = 1 */
1569  else
1570  kernel->width = kernel->height = (size_t) (2*args->rho+1);
1571  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1572  scale = args->sigma;
1573  }
1574  else {
1575  /* NOTE: user defaults set in "AcquireKernelInfo()" */
1576  if ( args->rho < 1.0 || args->sigma < 1.0 )
1577  return(DestroyKernelInfo(kernel)); /* invalid args given */
1578  kernel->width = (size_t)args->rho;
1579  kernel->height = (size_t)args->sigma;
1580  if ( args->xi < 0.0 || args->xi > (double)kernel->width ||
1581  args->psi < 0.0 || args->psi > (double)kernel->height )
1582  return(DestroyKernelInfo(kernel)); /* invalid args given */
1583  kernel->x = (ssize_t) args->xi;
1584  kernel->y = (ssize_t) args->psi;
1585  scale = 1.0;
1586  }
1587  kernel->values=(MagickRealType *) MagickAssumeAligned(
1588  AcquireAlignedMemory(kernel->width,kernel->height*
1589  sizeof(*kernel->values)));
1590  if (kernel->values == (MagickRealType *) NULL)
1591  return(DestroyKernelInfo(kernel));
1592 
1593  /* set all kernel values to scale given */
1594  u=(ssize_t) (kernel->width*kernel->height);
1595  for ( i=0; i < u; i++)
1596  kernel->values[i] = scale;
1597  kernel->minimum = kernel->maximum = scale; /* a flat shape */
1598  kernel->positive_range = scale*u;
1599  break;
1600  }
1601  case OctagonKernel:
1602  {
1603  if (args->rho < 1.0)
1604  kernel->width = kernel->height = 5; /* default radius = 2 */
1605  else
1606  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
1607  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1608 
1609  kernel->values=(MagickRealType *) MagickAssumeAligned(
1610  AcquireAlignedMemory(kernel->width,kernel->height*
1611  sizeof(*kernel->values)));
1612  if (kernel->values == (MagickRealType *) NULL)
1613  return(DestroyKernelInfo(kernel));
1614 
1615  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1616  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1617  if ( (labs((long) u)+labs((long) v)) <=
1618  ((long)kernel->x + (long)(kernel->x/2)) )
1619  kernel->positive_range += kernel->values[i] = args->sigma;
1620  else
1621  kernel->values[i] = nan;
1622  kernel->minimum = kernel->maximum = args->sigma; /* a flat shape */
1623  break;
1624  }
1625  case DiskKernel:
1626  {
1627  ssize_t
1628  limit = (ssize_t)(args->rho*args->rho);
1629 
1630  if (args->rho < 0.4) /* default radius approx 4.3 */
1631  kernel->width = kernel->height = 9L, limit = 18L;
1632  else
1633  kernel->width = kernel->height = (size_t)fabs(args->rho)*2+1;
1634  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1635 
1636  kernel->values=(MagickRealType *) MagickAssumeAligned(
1637  AcquireAlignedMemory(kernel->width,kernel->height*
1638  sizeof(*kernel->values)));
1639  if (kernel->values == (MagickRealType *) NULL)
1640  return(DestroyKernelInfo(kernel));
1641 
1642  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1643  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1644  if ((u*u+v*v) <= limit)
1645  kernel->positive_range += kernel->values[i] = args->sigma;
1646  else
1647  kernel->values[i] = nan;
1648  kernel->minimum = kernel->maximum = args->sigma; /* a flat shape */
1649  break;
1650  }
1651  case PlusKernel:
1652  {
1653  if (args->rho < 1.0)
1654  kernel->width = kernel->height = 5; /* default radius 2 */
1655  else
1656  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
1657  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1658 
1659  kernel->values=(MagickRealType *) MagickAssumeAligned(
1660  AcquireAlignedMemory(kernel->width,kernel->height*
1661  sizeof(*kernel->values)));
1662  if (kernel->values == (MagickRealType *) NULL)
1663  return(DestroyKernelInfo(kernel));
1664 
1665  /* set all kernel values along axises to given scale */
1666  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1667  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1668  kernel->values[i] = (u == 0 || v == 0) ? args->sigma : nan;
1669  kernel->minimum = kernel->maximum = args->sigma; /* a flat shape */
1670  kernel->positive_range = args->sigma*(kernel->width*2.0 - 1.0);
1671  break;
1672  }
1673  case CrossKernel:
1674  {
1675  if (args->rho < 1.0)
1676  kernel->width = kernel->height = 5; /* default radius 2 */
1677  else
1678  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
1679  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1680 
1681  kernel->values=(MagickRealType *) MagickAssumeAligned(
1682  AcquireAlignedMemory(kernel->width,kernel->height*
1683  sizeof(*kernel->values)));
1684  if (kernel->values == (MagickRealType *) NULL)
1685  return(DestroyKernelInfo(kernel));
1686 
1687  /* set all kernel values along axises to given scale */
1688  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
1689  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1690  kernel->values[i] = (u == v || u == -v) ? args->sigma : nan;
1691  kernel->minimum = kernel->maximum = args->sigma; /* a flat shape */
1692  kernel->positive_range = args->sigma*(kernel->width*2.0 - 1.0);
1693  break;
1694  }
1695  /*
1696  HitAndMiss Kernels
1697  */
1698  case RingKernel:
1699  case PeaksKernel:
1700  {
1701  ssize_t
1702  limit1,
1703  limit2,
1704  scale;
1705 
1706  if (args->rho < args->sigma)
1707  {
1708  kernel->width = ((size_t)args->sigma)*2+1;
1709  limit1 = (ssize_t)(args->rho*args->rho);
1710  limit2 = (ssize_t)(args->sigma*args->sigma);
1711  }
1712  else
1713  {
1714  kernel->width = ((size_t)args->rho)*2+1;
1715  limit1 = (ssize_t)(args->sigma*args->sigma);
1716  limit2 = (ssize_t)(args->rho*args->rho);
1717  }
1718  if ( limit2 <= 0 )
1719  kernel->width = 7L, limit1 = 7L, limit2 = 11L;
1720 
1721  kernel->height = kernel->width;
1722  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
1723  kernel->values=(MagickRealType *) MagickAssumeAligned(
1724  AcquireAlignedMemory(kernel->width,kernel->height*
1725  sizeof(*kernel->values)));
1726  if (kernel->values == (MagickRealType *) NULL)
1727  return(DestroyKernelInfo(kernel));
1728 
1729  /* set a ring of points of 'scale' ( 0.0 for PeaksKernel ) */
1730  scale = (ssize_t) (( type == PeaksKernel) ? 0.0 : args->xi);
1731  for ( i=0, v= -kernel->y; v <= (ssize_t)kernel->y; v++)
1732  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
1733  { ssize_t radius=u*u+v*v;
1734  if (limit1 < radius && radius <= limit2)
1735  kernel->positive_range += kernel->values[i] = (double) scale;
1736  else
1737  kernel->values[i] = nan;
1738  }
1739  kernel->minimum = kernel->maximum = (double) scale;
1740  if ( type == PeaksKernel ) {
1741  /* set the central point in the middle */
1742  kernel->values[kernel->x+kernel->y*kernel->width] = 1.0;
1743  kernel->positive_range = 1.0;
1744  kernel->maximum = 1.0;
1745  }
1746  break;
1747  }
1748  case EdgesKernel:
1749  {
1750  kernel=AcquireKernelInfo("ThinSE:482",exception);
1751  if (kernel == (KernelInfo *) NULL)
1752  return(kernel);
1753  kernel->type = type;
1754  ExpandMirrorKernelInfo(kernel); /* mirror expansion of kernels */
1755  break;
1756  }
1757  case CornersKernel:
1758  {
1759  kernel=AcquireKernelInfo("ThinSE:87",exception);
1760  if (kernel == (KernelInfo *) NULL)
1761  return(kernel);
1762  kernel->type = type;
1763  ExpandRotateKernelInfo(kernel, 90.0); /* Expand 90 degree rotations */
1764  break;
1765  }
1766  case DiagonalsKernel:
1767  {
1768  switch ( (int) args->rho ) {
1769  case 0:
1770  default:
1771  { KernelInfo
1772  *new_kernel;
1773  kernel=ParseKernelArray("3: 0,0,0 0,-,1 1,1,-");
1774  if (kernel == (KernelInfo *) NULL)
1775  return(kernel);
1776  kernel->type = type;
1777  new_kernel=ParseKernelArray("3: 0,0,1 0,-,1 0,1,-");
1778  if (new_kernel == (KernelInfo *) NULL)
1779  return(DestroyKernelInfo(kernel));
1780  new_kernel->type = type;
1781  LastKernelInfo(kernel)->next = new_kernel;
1782  ExpandMirrorKernelInfo(kernel);
1783  return(kernel);
1784  }
1785  case 1:
1786  kernel=ParseKernelArray("3: 0,0,0 0,-,1 1,1,-");
1787  break;
1788  case 2:
1789  kernel=ParseKernelArray("3: 0,0,1 0,-,1 0,1,-");
1790  break;
1791  }
1792  if (kernel == (KernelInfo *) NULL)
1793  return(kernel);
1794  kernel->type = type;
1795  RotateKernelInfo(kernel, args->sigma);
1796  break;
1797  }
1798  case LineEndsKernel:
1799  { /* Kernels for finding the end of thin lines */
1800  switch ( (int) args->rho ) {
1801  case 0:
1802  default:
1803  /* set of kernels to find all end of lines */
1804  return(AcquireKernelInfo("LineEnds:1>;LineEnds:2>",exception));
1805  case 1:
1806  /* kernel for 4-connected line ends - no rotation */
1807  kernel=ParseKernelArray("3: 0,0,- 0,1,1 0,0,-");
1808  break;
1809  case 2:
1810  /* kernel to add for 8-connected lines - no rotation */
1811  kernel=ParseKernelArray("3: 0,0,0 0,1,0 0,0,1");
1812  break;
1813  case 3:
1814  /* kernel to add for orthogonal line ends - does not find corners */
1815  kernel=ParseKernelArray("3: 0,0,0 0,1,1 0,0,0");
1816  break;
1817  case 4:
1818  /* traditional line end - fails on last T end */
1819  kernel=ParseKernelArray("3: 0,0,0 0,1,- 0,0,-");
1820  break;
1821  }
1822  if (kernel == (KernelInfo *) NULL)
1823  return(kernel);
1824  kernel->type = type;
1825  RotateKernelInfo(kernel, args->sigma);
1826  break;
1827  }
1828  case LineJunctionsKernel:
1829  { /* kernels for finding the junctions of multiple lines */
1830  switch ( (int) args->rho ) {
1831  case 0:
1832  default:
1833  /* set of kernels to find all line junctions */
1834  return(AcquireKernelInfo("LineJunctions:1@;LineJunctions:2>",exception));
1835  case 1:
1836  /* Y Junction */
1837  kernel=ParseKernelArray("3: 1,-,1 -,1,- -,1,-");
1838  break;
1839  case 2:
1840  /* Diagonal T Junctions */
1841  kernel=ParseKernelArray("3: 1,-,- -,1,- 1,-,1");
1842  break;
1843  case 3:
1844  /* Orthogonal T Junctions */
1845  kernel=ParseKernelArray("3: -,-,- 1,1,1 -,1,-");
1846  break;
1847  case 4:
1848  /* Diagonal X Junctions */
1849  kernel=ParseKernelArray("3: 1,-,1 -,1,- 1,-,1");
1850  break;
1851  case 5:
1852  /* Orthogonal X Junctions - minimal diamond kernel */
1853  kernel=ParseKernelArray("3: -,1,- 1,1,1 -,1,-");
1854  break;
1855  }
1856  if (kernel == (KernelInfo *) NULL)
1857  return(kernel);
1858  kernel->type = type;
1859  RotateKernelInfo(kernel, args->sigma);
1860  break;
1861  }
1862  case RidgesKernel:
1863  { /* Ridges - Ridge finding kernels */
1864  KernelInfo
1865  *new_kernel;
1866  switch ( (int) args->rho ) {
1867  case 1:
1868  default:
1869  kernel=ParseKernelArray("3x1:0,1,0");
1870  if (kernel == (KernelInfo *) NULL)
1871  return(kernel);
1872  kernel->type = type;
1873  ExpandRotateKernelInfo(kernel, 90.0); /* 2 rotated kernels (symmetrical) */
1874  break;
1875  case 2:
1876  kernel=ParseKernelArray("4x1:0,1,1,0");
1877  if (kernel == (KernelInfo *) NULL)
1878  return(kernel);
1879  kernel->type = type;
1880  ExpandRotateKernelInfo(kernel, 90.0); /* 4 rotated kernels */
1881 
1882  /* Kernels to find a stepped 'thick' line, 4 rotates + mirrors */
1883  /* Unfortunatally we can not yet rotate a non-square kernel */
1884  /* But then we can't flip a non-symetrical kernel either */
1885  new_kernel=ParseKernelArray("4x3+1+1:0,1,1,- -,1,1,- -,1,1,0");
1886  if (new_kernel == (KernelInfo *) NULL)
1887  return(DestroyKernelInfo(kernel));
1888  new_kernel->type = type;
1889  LastKernelInfo(kernel)->next = new_kernel;
1890  new_kernel=ParseKernelArray("4x3+2+1:0,1,1,- -,1,1,- -,1,1,0");
1891  if (new_kernel == (KernelInfo *) NULL)
1892  return(DestroyKernelInfo(kernel));
1893  new_kernel->type = type;
1894  LastKernelInfo(kernel)->next = new_kernel;
1895  new_kernel=ParseKernelArray("4x3+1+1:-,1,1,0 -,1,1,- 0,1,1,-");
1896  if (new_kernel == (KernelInfo *) NULL)
1897  return(DestroyKernelInfo(kernel));
1898  new_kernel->type = type;
1899  LastKernelInfo(kernel)->next = new_kernel;
1900  new_kernel=ParseKernelArray("4x3+2+1:-,1,1,0 -,1,1,- 0,1,1,-");
1901  if (new_kernel == (KernelInfo *) NULL)
1902  return(DestroyKernelInfo(kernel));
1903  new_kernel->type = type;
1904  LastKernelInfo(kernel)->next = new_kernel;
1905  new_kernel=ParseKernelArray("3x4+1+1:0,-,- 1,1,1 1,1,1 -,-,0");
1906  if (new_kernel == (KernelInfo *) NULL)
1907  return(DestroyKernelInfo(kernel));
1908  new_kernel->type = type;
1909  LastKernelInfo(kernel)->next = new_kernel;
1910  new_kernel=ParseKernelArray("3x4+1+2:0,-,- 1,1,1 1,1,1 -,-,0");
1911  if (new_kernel == (KernelInfo *) NULL)
1912  return(DestroyKernelInfo(kernel));
1913  new_kernel->type = type;
1914  LastKernelInfo(kernel)->next = new_kernel;
1915  new_kernel=ParseKernelArray("3x4+1+1:-,-,0 1,1,1 1,1,1 0,-,-");
1916  if (new_kernel == (KernelInfo *) NULL)
1917  return(DestroyKernelInfo(kernel));
1918  new_kernel->type = type;
1919  LastKernelInfo(kernel)->next = new_kernel;
1920  new_kernel=ParseKernelArray("3x4+1+2:-,-,0 1,1,1 1,1,1 0,-,-");
1921  if (new_kernel == (KernelInfo *) NULL)
1922  return(DestroyKernelInfo(kernel));
1923  new_kernel->type = type;
1924  LastKernelInfo(kernel)->next = new_kernel;
1925  break;
1926  }
1927  break;
1928  }
1929  case ConvexHullKernel:
1930  {
1931  KernelInfo
1932  *new_kernel;
1933  /* first set of 8 kernels */
1934  kernel=ParseKernelArray("3: 1,1,- 1,0,- 1,-,0");
1935  if (kernel == (KernelInfo *) NULL)
1936  return(kernel);
1937  kernel->type = type;
1938  ExpandRotateKernelInfo(kernel, 90.0);
1939  /* append the mirror versions too - no flip function yet */
1940  new_kernel=ParseKernelArray("3: 1,1,1 1,0,- -,-,0");
1941  if (new_kernel == (KernelInfo *) NULL)
1942  return(DestroyKernelInfo(kernel));
1943  new_kernel->type = type;
1944  ExpandRotateKernelInfo(new_kernel, 90.0);
1945  LastKernelInfo(kernel)->next = new_kernel;
1946  break;
1947  }
1948  case SkeletonKernel:
1949  {
1950  switch ( (int) args->rho ) {
1951  case 1:
1952  default:
1953  /* Traditional Skeleton...
1954  ** A cyclically rotated single kernel
1955  */
1956  kernel=AcquireKernelInfo("ThinSE:482",exception);
1957  if (kernel == (KernelInfo *) NULL)
1958  return(kernel);
1959  kernel->type = type;
1960  ExpandRotateKernelInfo(kernel, 45.0); /* 8 rotations */
1961  break;
1962  case 2:
1963  /* HIPR Variation of the cyclic skeleton
1964  ** Corners of the traditional method made more forgiving,
1965  ** but the retain the same cyclic order.
1966  */
1967  kernel=AcquireKernelInfo("ThinSE:482; ThinSE:87x90;",exception);
1968  if (kernel == (KernelInfo *) NULL)
1969  return(kernel);
1970  if (kernel->next == (KernelInfo *) NULL)
1971  return(DestroyKernelInfo(kernel));
1972  kernel->type = type;
1973  kernel->next->type = type;
1974  ExpandRotateKernelInfo(kernel, 90.0); /* 4 rotations of the 2 kernels */
1975  break;
1976  case 3:
1977  /* Dan Bloomberg Skeleton, from his paper on 3x3 thinning SE's
1978  ** "Connectivity-Preserving Morphological Image Thransformations"
1979  ** by Dan S. Bloomberg, available on Leptonica, Selected Papers,
1980  ** http://www.leptonica.com/papers/conn.pdf
1981  */
1982  kernel=AcquireKernelInfo("ThinSE:41; ThinSE:42; ThinSE:43",
1983  exception);
1984  if (kernel == (KernelInfo *) NULL)
1985  return(kernel);
1986  if (kernel->next == (KernelInfo *) NULL)
1987  return(DestroyKernelInfo(kernel));
1988  if (kernel->next->next == (KernelInfo *) NULL)
1989  return(DestroyKernelInfo(kernel));
1990  kernel->type = type;
1991  kernel->next->type = type;
1992  kernel->next->next->type = type;
1993  ExpandMirrorKernelInfo(kernel); /* 12 kernels total */
1994  break;
1995  }
1996  break;
1997  }
1998  case ThinSEKernel:
1999  { /* Special kernels for general thinning, while preserving connections
2000  ** "Connectivity-Preserving Morphological Image Thransformations"
2001  ** by Dan S. Bloomberg, available on Leptonica, Selected Papers,
2002  ** http://www.leptonica.com/papers/conn.pdf
2003  ** And
2004  ** http://tpgit.github.com/Leptonica/ccthin_8c_source.html
2005  **
2006  ** Note kernels do not specify the origin pixel, allowing them
2007  ** to be used for both thickening and thinning operations.
2008  */
2009  switch ( (int) args->rho ) {
2010  /* SE for 4-connected thinning */
2011  case 41: /* SE_4_1 */
2012  kernel=ParseKernelArray("3: -,-,1 0,-,1 -,-,1");
2013  break;
2014  case 42: /* SE_4_2 */
2015  kernel=ParseKernelArray("3: -,-,1 0,-,1 -,0,-");
2016  break;
2017  case 43: /* SE_4_3 */
2018  kernel=ParseKernelArray("3: -,0,- 0,-,1 -,-,1");
2019  break;
2020  case 44: /* SE_4_4 */
2021  kernel=ParseKernelArray("3: -,0,- 0,-,1 -,0,-");
2022  break;
2023  case 45: /* SE_4_5 */
2024  kernel=ParseKernelArray("3: -,0,1 0,-,1 -,0,-");
2025  break;
2026  case 46: /* SE_4_6 */
2027  kernel=ParseKernelArray("3: -,0,- 0,-,1 -,0,1");
2028  break;
2029  case 47: /* SE_4_7 */
2030  kernel=ParseKernelArray("3: -,1,1 0,-,1 -,0,-");
2031  break;
2032  case 48: /* SE_4_8 */
2033  kernel=ParseKernelArray("3: -,-,1 0,-,1 0,-,1");
2034  break;
2035  case 49: /* SE_4_9 */
2036  kernel=ParseKernelArray("3: 0,-,1 0,-,1 -,-,1");
2037  break;
2038  /* SE for 8-connected thinning - negatives of the above */
2039  case 81: /* SE_8_0 */
2040  kernel=ParseKernelArray("3: -,1,- 0,-,1 -,1,-");
2041  break;
2042  case 82: /* SE_8_2 */
2043  kernel=ParseKernelArray("3: -,1,- 0,-,1 0,-,-");
2044  break;
2045  case 83: /* SE_8_3 */
2046  kernel=ParseKernelArray("3: 0,-,- 0,-,1 -,1,-");
2047  break;
2048  case 84: /* SE_8_4 */
2049  kernel=ParseKernelArray("3: 0,-,- 0,-,1 0,-,-");
2050  break;
2051  case 85: /* SE_8_5 */
2052  kernel=ParseKernelArray("3: 0,-,1 0,-,1 0,-,-");
2053  break;
2054  case 86: /* SE_8_6 */
2055  kernel=ParseKernelArray("3: 0,-,- 0,-,1 0,-,1");
2056  break;
2057  case 87: /* SE_8_7 */
2058  kernel=ParseKernelArray("3: -,1,- 0,-,1 0,0,-");
2059  break;
2060  case 88: /* SE_8_8 */
2061  kernel=ParseKernelArray("3: -,1,- 0,-,1 0,1,-");
2062  break;
2063  case 89: /* SE_8_9 */
2064  kernel=ParseKernelArray("3: 0,1,- 0,-,1 -,1,-");
2065  break;
2066  /* Special combined SE kernels */
2067  case 423: /* SE_4_2 , SE_4_3 Combined Kernel */
2068  kernel=ParseKernelArray("3: -,-,1 0,-,- -,0,-");
2069  break;
2070  case 823: /* SE_8_2 , SE_8_3 Combined Kernel */
2071  kernel=ParseKernelArray("3: -,1,- -,-,1 0,-,-");
2072  break;
2073  case 481: /* SE_48_1 - General Connected Corner Kernel */
2074  kernel=ParseKernelArray("3: -,1,1 0,-,1 0,0,-");
2075  break;
2076  default:
2077  case 482: /* SE_48_2 - General Edge Kernel */
2078  kernel=ParseKernelArray("3: 0,-,1 0,-,1 0,-,1");
2079  break;
2080  }
2081  if (kernel == (KernelInfo *) NULL)
2082  return(kernel);
2083  kernel->type = type;
2084  RotateKernelInfo(kernel, args->sigma);
2085  break;
2086  }
2087  /*
2088  Distance Measuring Kernels
2089  */
2090  case ChebyshevKernel:
2091  {
2092  if (args->rho < 1.0)
2093  kernel->width = kernel->height = 3; /* default radius = 1 */
2094  else
2095  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
2096  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
2097 
2098  kernel->values=(MagickRealType *) MagickAssumeAligned(
2099  AcquireAlignedMemory(kernel->width,kernel->height*
2100  sizeof(*kernel->values)));
2101  if (kernel->values == (MagickRealType *) NULL)
2102  return(DestroyKernelInfo(kernel));
2103 
2104  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
2105  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
2106  kernel->positive_range += ( kernel->values[i] =
2107  args->sigma*MagickMax(fabs((double)u),fabs((double)v)) );
2108  kernel->maximum = kernel->values[0];
2109  break;
2110  }
2111  case ManhattanKernel:
2112  {
2113  if (args->rho < 1.0)
2114  kernel->width = kernel->height = 3; /* default radius = 1 */
2115  else
2116  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
2117  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
2118 
2119  kernel->values=(MagickRealType *) MagickAssumeAligned(
2120  AcquireAlignedMemory(kernel->width,kernel->height*
2121  sizeof(*kernel->values)));
2122  if (kernel->values == (MagickRealType *) NULL)
2123  return(DestroyKernelInfo(kernel));
2124 
2125  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
2126  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
2127  kernel->positive_range += ( kernel->values[i] =
2128  args->sigma*(labs((long) u)+labs((long) v)) );
2129  kernel->maximum = kernel->values[0];
2130  break;
2131  }
2132  case OctagonalKernel:
2133  {
2134  if (args->rho < 2.0)
2135  kernel->width = kernel->height = 5; /* default/minimum radius = 2 */
2136  else
2137  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
2138  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
2139 
2140  kernel->values=(MagickRealType *) MagickAssumeAligned(
2141  AcquireAlignedMemory(kernel->width,kernel->height*
2142  sizeof(*kernel->values)));
2143  if (kernel->values == (MagickRealType *) NULL)
2144  return(DestroyKernelInfo(kernel));
2145 
2146  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
2147  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
2148  {
2149  double
2150  r1 = MagickMax(fabs((double)u),fabs((double)v)),
2151  r2 = floor((double)(labs((long)u)+labs((long)v)+1)/1.5);
2152  kernel->positive_range += kernel->values[i] =
2153  args->sigma*MagickMax(r1,r2);
2154  }
2155  kernel->maximum = kernel->values[0];
2156  break;
2157  }
2158  case EuclideanKernel:
2159  {
2160  if (args->rho < 1.0)
2161  kernel->width = kernel->height = 3; /* default radius = 1 */
2162  else
2163  kernel->width = kernel->height = ((size_t)args->rho)*2+1;
2164  kernel->x = kernel->y = (ssize_t) (kernel->width-1)/2;
2165 
2166  kernel->values=(MagickRealType *) MagickAssumeAligned(
2167  AcquireAlignedMemory(kernel->width,kernel->height*
2168  sizeof(*kernel->values)));
2169  if (kernel->values == (MagickRealType *) NULL)
2170  return(DestroyKernelInfo(kernel));
2171 
2172  for ( i=0, v=-kernel->y; v <= (ssize_t)kernel->y; v++)
2173  for ( u=-kernel->x; u <= (ssize_t)kernel->x; u++, i++)
2174  kernel->positive_range += ( kernel->values[i] =
2175  args->sigma*sqrt((double)(u*u+v*v)) );
2176  kernel->maximum = kernel->values[0];
2177  break;
2178  }
2179  default:
2180  {
2181  /* No-Op Kernel - Basically just a single pixel on its own */
2182  kernel=ParseKernelArray("1:1");
2183  if (kernel == (KernelInfo *) NULL)
2184  return(kernel);
2185  kernel->type = UndefinedKernel;
2186  break;
2187  }
2188  break;
2189  }
2190  return(kernel);
2191 }
2192 ␌
2193 /*
2194 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2195 % %
2196 % %
2197 % %
2198 % C l o n e K e r n e l I n f o %
2199 % %
2200 % %
2201 % %
2202 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2203 %
2204 % CloneKernelInfo() creates a new clone of the given Kernel List so that its
2205 % can be modified without effecting the original. The cloned kernel should
2206 % be destroyed using DestoryKernelInfo() when no longer needed.
2207 %
2208 % The format of the CloneKernelInfo method is:
2209 %
2210 % KernelInfo *CloneKernelInfo(const KernelInfo *kernel)
2211 %
2212 % A description of each parameter follows:
2213 %
2214 % o kernel: the Morphology/Convolution kernel to be cloned
2215 %
2216 */
2217 MagickExport KernelInfo *CloneKernelInfo(const KernelInfo *kernel)
2218 {
2219  ssize_t
2220  i;
2221 
2222  KernelInfo
2223  *new_kernel;
2224 
2225  assert(kernel != (KernelInfo *) NULL);
2226  new_kernel=(KernelInfo *) AcquireMagickMemory(sizeof(*kernel));
2227  if (new_kernel == (KernelInfo *) NULL)
2228  return(new_kernel);
2229  *new_kernel=(*kernel); /* copy values in structure */
2230 
2231  /* replace the values with a copy of the values */
2232  new_kernel->values=(MagickRealType *) MagickAssumeAligned(
2233  AcquireAlignedMemory(kernel->width,kernel->height*sizeof(*kernel->values)));
2234  if (new_kernel->values == (MagickRealType *) NULL)
2235  return(DestroyKernelInfo(new_kernel));
2236  for (i=0; i < (ssize_t) (kernel->width*kernel->height); i++)
2237  new_kernel->values[i]=kernel->values[i];
2238 
2239  /* Also clone the next kernel in the kernel list */
2240  if ( kernel->next != (KernelInfo *) NULL ) {
2241  new_kernel->next = CloneKernelInfo(kernel->next);
2242  if ( new_kernel->next == (KernelInfo *) NULL )
2243  return(DestroyKernelInfo(new_kernel));
2244  }
2245 
2246  return(new_kernel);
2247 }
2248 ␌
2249 /*
2250 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2251 % %
2252 % %
2253 % %
2254 % D e s t r o y K e r n e l I n f o %
2255 % %
2256 % %
2257 % %
2258 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2259 %
2260 % DestroyKernelInfo() frees the memory used by a Convolution/Morphology
2261 % kernel.
2262 %
2263 % The format of the DestroyKernelInfo method is:
2264 %
2265 % KernelInfo *DestroyKernelInfo(KernelInfo *kernel)
2266 %
2267 % A description of each parameter follows:
2268 %
2269 % o kernel: the Morphology/Convolution kernel to be destroyed
2270 %
2271 */
2272 MagickExport KernelInfo *DestroyKernelInfo(KernelInfo *kernel)
2273 {
2274  assert(kernel != (KernelInfo *) NULL);
2275  if (kernel->next != (KernelInfo *) NULL)
2276  kernel->next=DestroyKernelInfo(kernel->next);
2277  kernel->values=(MagickRealType *) RelinquishAlignedMemory(kernel->values);
2278  kernel=(KernelInfo *) RelinquishMagickMemory(kernel);
2279  return(kernel);
2280 }
2281 ␌
2282 /*
2283 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2284 % %
2285 % %
2286 % %
2287 + E x p a n d M i r r o r K e r n e l I n f o %
2288 % %
2289 % %
2290 % %
2291 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2292 %
2293 % ExpandMirrorKernelInfo() takes a single kernel, and expands it into a
2294 % sequence of 90-degree rotated kernels but providing a reflected 180
2295 % rotatation, before the -/+ 90-degree rotations.
2296 %
2297 % This special rotation order produces a better, more symetrical thinning of
2298 % objects.
2299 %
2300 % The format of the ExpandMirrorKernelInfo method is:
2301 %
2302 % void ExpandMirrorKernelInfo(KernelInfo *kernel)
2303 %
2304 % A description of each parameter follows:
2305 %
2306 % o kernel: the Morphology/Convolution kernel
2307 %
2308 % This function is only internel to this module, as it is not finalized,
2309 % especially with regard to non-orthogonal angles, and rotation of larger
2310 % 2D kernels.
2311 */
2312 
2313 #if 0
2314 static void FlopKernelInfo(KernelInfo *kernel)
2315  { /* Do a Flop by reversing each row. */
2316  size_t
2317  y;
2318  ssize_t
2319  x,r;
2320  double
2321  *k,t;
2322 
2323  for ( y=0, k=kernel->values; y < kernel->height; y++, k+=kernel->width)
2324  for ( x=0, r=kernel->width-1; x<kernel->width/2; x++, r--)
2325  t=k[x], k[x]=k[r], k[r]=t;
2326 
2327  kernel->x = kernel->width - kernel->x - 1;
2328  angle = fmod(angle+180.0, 360.0);
2329  }
2330 #endif
2331 
2332 static void ExpandMirrorKernelInfo(KernelInfo *kernel)
2333 {
2334  KernelInfo
2335  *clone,
2336  *last;
2337 
2338  last = kernel;
2339 
2340  clone = CloneKernelInfo(last);
2341  if (clone == (KernelInfo *) NULL)
2342  return;
2343  RotateKernelInfo(clone, 180); /* flip */
2344  LastKernelInfo(last)->next = clone;
2345  last = clone;
2346 
2347  clone = CloneKernelInfo(last);
2348  if (clone == (KernelInfo *) NULL)
2349  return;
2350  RotateKernelInfo(clone, 90); /* transpose */
2351  LastKernelInfo(last)->next = clone;
2352  last = clone;
2353 
2354  clone = CloneKernelInfo(last);
2355  if (clone == (KernelInfo *) NULL)
2356  return;
2357  RotateKernelInfo(clone, 180); /* flop */
2358  LastKernelInfo(last)->next = clone;
2359 
2360  return;
2361 }
2362 ␌
2363 /*
2364 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2365 % %
2366 % %
2367 % %
2368 + E x p a n d R o t a t e K e r n e l I n f o %
2369 % %
2370 % %
2371 % %
2372 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2373 %
2374 % ExpandRotateKernelInfo() takes a kernel list, and expands it by rotating
2375 % incrementally by the angle given, until the kernel repeats.
2376 %
2377 % WARNING: 45 degree rotations only works for 3x3 kernels.
2378 % While 90 degree roatations only works for linear and square kernels
2379 %
2380 % The format of the ExpandRotateKernelInfo method is:
2381 %
2382 % void ExpandRotateKernelInfo(KernelInfo *kernel, double angle)
2383 %
2384 % A description of each parameter follows:
2385 %
2386 % o kernel: the Morphology/Convolution kernel
2387 %
2388 % o angle: angle to rotate in degrees
2389 %
2390 % This function is only internel to this module, as it is not finalized,
2391 % especially with regard to non-orthogonal angles, and rotation of larger
2392 % 2D kernels.
2393 */
2394 
2395 /* Internal Routine - Return true if two kernels are the same */
2396 static MagickBooleanType SameKernelInfo(const KernelInfo *kernel1,
2397  const KernelInfo *kernel2)
2398 {
2399  size_t
2400  i;
2401 
2402  /* check size and origin location */
2403  if ( kernel1->width != kernel2->width
2404  || kernel1->height != kernel2->height
2405  || kernel1->x != kernel2->x
2406  || kernel1->y != kernel2->y )
2407  return MagickFalse;
2408 
2409  /* check actual kernel values */
2410  for (i=0; i < (kernel1->width*kernel1->height); i++) {
2411  /* Test for Nan equivalence */
2412  if ( IsNaN(kernel1->values[i]) && !IsNaN(kernel2->values[i]) )
2413  return MagickFalse;
2414  if ( IsNaN(kernel2->values[i]) && !IsNaN(kernel1->values[i]) )
2415  return MagickFalse;
2416  /* Test actual values are equivalent */
2417  if ( fabs(kernel1->values[i] - kernel2->values[i]) >= MagickEpsilon )
2418  return MagickFalse;
2419  }
2420 
2421  return MagickTrue;
2422 }
2423 
2424 static void ExpandRotateKernelInfo(KernelInfo *kernel,const double angle)
2425 {
2426  KernelInfo
2427  *clone_info,
2428  *last;
2429 
2430  clone_info=(KernelInfo *) NULL;
2431  last=kernel;
2432 DisableMSCWarning(4127)
2433  while (1) {
2434 RestoreMSCWarning
2435  clone_info=CloneKernelInfo(last);
2436  if (clone_info == (KernelInfo *) NULL)
2437  break;
2438  RotateKernelInfo(clone_info,angle);
2439  if (SameKernelInfo(kernel,clone_info) != MagickFalse)
2440  break;
2441  LastKernelInfo(last)->next=clone_info;
2442  last=clone_info;
2443  }
2444  if (clone_info != (KernelInfo *) NULL)
2445  clone_info=DestroyKernelInfo(clone_info); /* kernel repeated - junk */
2446  return;
2447 }
2448 ␌
2449 /*
2450 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2451 % %
2452 % %
2453 % %
2454 + C a l c M e t a K e r n a l I n f o %
2455 % %
2456 % %
2457 % %
2458 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2459 %
2460 % CalcKernelMetaData() recalculate the KernelInfo meta-data of this kernel only,
2461 % using the kernel values. This should only ne used if it is not possible to
2462 % calculate that meta-data in some easier way.
2463 %
2464 % It is important that the meta-data is correct before ScaleKernelInfo() is
2465 % used to perform kernel normalization.
2466 %
2467 % The format of the CalcKernelMetaData method is:
2468 %
2469 % void CalcKernelMetaData(KernelInfo *kernel, const double scale )
2470 %
2471 % A description of each parameter follows:
2472 %
2473 % o kernel: the Morphology/Convolution kernel to modify
2474 %
2475 % WARNING: Minimum and Maximum values are assumed to include zero, even if
2476 % zero is not part of the kernel (as in Gaussian Derived kernels). This
2477 % however is not true for flat-shaped morphological kernels.
2478 %
2479 % WARNING: Only the specific kernel pointed to is modified, not a list of
2480 % multiple kernels.
2481 %
2482 % This is an internal function and not expected to be useful outside this
2483 % module. This could change however.
2484 */
2485 static void CalcKernelMetaData(KernelInfo *kernel)
2486 {
2487  size_t
2488  i;
2489 
2490  kernel->minimum = kernel->maximum = 0.0;
2491  kernel->negative_range = kernel->positive_range = 0.0;
2492  for (i=0; i < (kernel->width*kernel->height); i++)
2493  {
2494  if ( fabs(kernel->values[i]) < MagickEpsilon )
2495  kernel->values[i] = 0.0;
2496  ( kernel->values[i] < 0)
2497  ? ( kernel->negative_range += kernel->values[i] )
2498  : ( kernel->positive_range += kernel->values[i] );
2499  Minimize(kernel->minimum, kernel->values[i]);
2500  Maximize(kernel->maximum, kernel->values[i]);
2501  }
2502 
2503  return;
2504 }
2505 ␌
2506 /*
2507 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2508 % %
2509 % %
2510 % %
2511 % M o r p h o l o g y A p p l y %
2512 % %
2513 % %
2514 % %
2515 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2516 %
2517 % MorphologyApply() applies a morphological method, multiple times using
2518 % a list of multiple kernels. This is the method that should be called by
2519 % other 'operators' that internally use morphology operations as part of
2520 % their processing.
2521 %
2522 % It is basically equivalent to as MorphologyImage() (see below) but without
2523 % any user controls. This allows internel programs to use this method to
2524 % perform a specific task without possible interference by any API user
2525 % supplied settings.
2526 %
2527 % It is MorphologyImage() task to extract any such user controls, and
2528 % pass them to this function for processing.
2529 %
2530 % More specifically all given kernels should already be scaled, normalised,
2531 % and blended appropriatally before being parred to this routine. The
2532 % appropriate bias, and compose (typically 'UndefinedComposeOp') given.
2533 %
2534 % The format of the MorphologyApply method is:
2535 %
2536 % Image *MorphologyApply(const Image *image,MorphologyMethod method,
2537 % const ssize_t iterations,const KernelInfo *kernel,
2538 % const CompositeMethod compose,const double bias,
2539 % ExceptionInfo *exception)
2540 %
2541 % A description of each parameter follows:
2542 %
2543 % o image: the source image
2544 %
2545 % o method: the morphology method to be applied.
2546 %
2547 % o iterations: apply the operation this many times (or no change).
2548 % A value of -1 means loop until no change found.
2549 % How this is applied may depend on the morphology method.
2550 % Typically this is a value of 1.
2551 %
2552 % o channel: the channel type.
2553 %
2554 % o kernel: An array of double representing the morphology kernel.
2555 %
2556 % o compose: How to handle or merge multi-kernel results.
2557 % If 'UndefinedCompositeOp' use default for the Morphology method.
2558 % If 'NoCompositeOp' force image to be re-iterated by each kernel.
2559 % Otherwise merge the results using the compose method given.
2560 %
2561 % o bias: Convolution Output Bias.
2562 %
2563 % o exception: return any errors or warnings in this structure.
2564 %
2565 */
2566 static ssize_t MorphologyPrimitive(const Image *image,Image *morphology_image,
2567  const MorphologyMethod method,const KernelInfo *kernel,const double bias,
2568  ExceptionInfo *exception)
2569 {
2570 #define MorphologyTag "Morphology/Image"
2571 
2572  CacheView
2573  *image_view,
2574  *morphology_view;
2575 
2576  MagickBooleanType
2577  status;
2578 
2579  MagickOffsetType
2580  progress;
2581 
2582  OffsetInfo
2583  offset;
2584 
2585  ssize_t
2586  j,
2587  y;
2588 
2589  size_t
2590  changed,
2591  *changes,
2592  width;
2593 
2594  /*
2595  Some methods (including convolve) needs to use a reflected kernel.
2596  Adjust 'origin' offsets to loop though kernel as a reflection.
2597  */
2598  assert(image != (Image *) NULL);
2599  assert(image->signature == MagickCoreSignature);
2600  assert(morphology_image != (Image *) NULL);
2601  assert(morphology_image->signature == MagickCoreSignature);
2602  assert(kernel != (KernelInfo *) NULL);
2603  assert(kernel->signature == MagickCoreSignature);
2604  assert(exception != (ExceptionInfo *) NULL);
2605  assert(exception->signature == MagickCoreSignature);
2606  status=MagickTrue;
2607  progress=0;
2608  image_view=AcquireVirtualCacheView(image,exception);
2609  morphology_view=AcquireAuthenticCacheView(morphology_image,exception);
2610  width=image->columns+kernel->width-1;
2611  offset.x=0;
2612  offset.y=0;
2613  switch (method)
2614  {
2615  case ConvolveMorphology:
2616  case DilateMorphology:
2617  case DilateIntensityMorphology:
2618  case IterativeDistanceMorphology:
2619  {
2620  /*
2621  Kernel needs to use a reflection about origin.
2622  */
2623  offset.x=(ssize_t) kernel->width-kernel->x-1;
2624  offset.y=(ssize_t) kernel->height-kernel->y-1;
2625  break;
2626  }
2627  case ErodeMorphology:
2628  case ErodeIntensityMorphology:
2629  case HitAndMissMorphology:
2630  case ThinningMorphology:
2631  case ThickenMorphology:
2632  {
2633  /*
2634  Use kernel as is, not reflection required.
2635  */
2636  offset.x=kernel->x;
2637  offset.y=kernel->y;
2638  break;
2639  }
2640  default:
2641  {
2642  ThrowMagickException(exception,GetMagickModule(),OptionWarning,
2643  "InvalidOption","`%s'","not a primitive morphology method");
2644  break;
2645  }
2646  }
2647  changed=0;
2648  changes=(size_t *) AcquireQuantumMemory(GetOpenMPMaximumThreads(),
2649  sizeof(*changes));
2650  if (changes == (size_t *) NULL)
2651  ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
2652  for (j=0; j < (ssize_t) GetOpenMPMaximumThreads(); j++)
2653  changes[j]=0;
2654  if ((method == ConvolveMorphology) && (kernel->width == 1))
2655  {
2656  ssize_t
2657  x;
2658 
2659  /*
2660  Special handling (for speed) of vertical (blur) kernels. This performs
2661  its handling in columns rather than in rows. This is only done
2662  for convolve as it is the only method that generates very large 1-D
2663  vertical kernels (such as a 'BlurKernel')
2664  */
2665 #if defined(MAGICKCORE_OPENMP_SUPPORT)
2666  #pragma omp parallel for schedule(static) shared(progress,status) \
2667  magick_number_threads(image,morphology_image,image->columns,1)
2668 #endif
2669  for (x=0; x < (ssize_t) image->columns; x++)
2670  {
2671  const int
2672  id = GetOpenMPThreadId();
2673 
2674  const Quantum
2675  *magick_restrict p;
2676 
2677  Quantum
2678  *magick_restrict q;
2679 
2680  ssize_t
2681  center,
2682  r;
2683 
2684  if (status == MagickFalse)
2685  continue;
2686  p=GetCacheViewVirtualPixels(image_view,x,-offset.y,1,image->rows+
2687  kernel->height-1,exception);
2688  q=GetCacheViewAuthenticPixels(morphology_view,x,0,1,
2689  morphology_image->rows,exception);
2690  if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
2691  {
2692  status=MagickFalse;
2693  continue;
2694  }
2695  center=(ssize_t) GetPixelChannels(image)*offset.y;
2696  for (r=0; r < (ssize_t) image->rows; r++)
2697  {
2698  ssize_t
2699  i;
2700 
2701  for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
2702  {
2703  double
2704  alpha,
2705  gamma,
2706  pixel;
2707 
2708  PixelChannel
2709  channel;
2710 
2711  PixelTrait
2712  morphology_traits,
2713  traits;
2714 
2715  const MagickRealType
2716  *magick_restrict k;
2717 
2718  const Quantum
2719  *magick_restrict pixels;
2720 
2721  ssize_t
2722  v;
2723 
2724  size_t
2725  count;
2726 
2727  channel=GetPixelChannelChannel(image,i);
2728  traits=GetPixelChannelTraits(image,channel);
2729  morphology_traits=GetPixelChannelTraits(morphology_image,channel);
2730  if ((traits == UndefinedPixelTrait) ||
2731  (morphology_traits == UndefinedPixelTrait))
2732  continue;
2733  if ((traits & CopyPixelTrait) != 0)
2734  {
2735  SetPixelChannel(morphology_image,channel,p[center+i],q);
2736  continue;
2737  }
2738  k=(&kernel->values[kernel->height-1]);
2739  pixels=p;
2740  pixel=bias;
2741  gamma=1.0;
2742  count=0;
2743  if (((image->alpha_trait & BlendPixelTrait) == 0) ||
2744  ((morphology_traits & BlendPixelTrait) == 0))
2745  for (v=0; v < (ssize_t) kernel->height; v++)
2746  {
2747  if (!IsNaN(*k))
2748  {
2749  pixel+=(*k)*pixels[i];
2750  count++;
2751  }
2752  k--;
2753  pixels+=GetPixelChannels(image);
2754  }
2755  else
2756  {
2757  gamma=0.0;
2758  for (v=0; v < (ssize_t) kernel->height; v++)
2759  {
2760  if (!IsNaN(*k))
2761  {
2762  alpha=(double) (QuantumScale*GetPixelAlpha(image,pixels));
2763  pixel+=alpha*(*k)*pixels[i];
2764  gamma+=alpha*(*k);
2765  count++;
2766  }
2767  k--;
2768  pixels+=GetPixelChannels(image);
2769  }
2770  }
2771  if (fabs(pixel-p[center+i]) >= MagickEpsilon)
2772  changes[id]++;
2773  gamma=PerceptibleReciprocal(gamma);
2774  if (count != 0)
2775  gamma*=(double) kernel->height/count;
2776  SetPixelChannel(morphology_image,channel,ClampToQuantum(gamma*
2777  pixel),q);
2778  }
2779  p+=GetPixelChannels(image);
2780  q+=GetPixelChannels(morphology_image);
2781  }
2782  if (SyncCacheViewAuthenticPixels(morphology_view,exception) == MagickFalse)
2783  status=MagickFalse;
2784  if (image->progress_monitor != (MagickProgressMonitor) NULL)
2785  {
2786  MagickBooleanType
2787  proceed;
2788 
2789 #if defined(MAGICKCORE_OPENMP_SUPPORT)
2790  #pragma omp atomic
2791 #endif
2792  progress++;
2793  proceed=SetImageProgress(image,MorphologyTag,progress,image->rows);
2794  if (proceed == MagickFalse)
2795  status=MagickFalse;
2796  }
2797  }
2798  morphology_image->type=image->type;
2799  morphology_view=DestroyCacheView(morphology_view);
2800  image_view=DestroyCacheView(image_view);
2801  for (j=0; j < (ssize_t) GetOpenMPMaximumThreads(); j++)
2802  changed+=changes[j];
2803  changes=(size_t *) RelinquishMagickMemory(changes);
2804  return(status ? (ssize_t) changed/GetImageChannels(image) : 0);
2805  }
2806  /*
2807  Normal handling of horizontal or rectangular kernels (row by row).
2808  */
2809 #if defined(MAGICKCORE_OPENMP_SUPPORT)
2810  #pragma omp parallel for schedule(static) shared(progress,status) \
2811  magick_number_threads(image,morphology_image,image->rows,1)
2812 #endif
2813  for (y=0; y < (ssize_t) image->rows; y++)
2814  {
2815  const int
2816  id = GetOpenMPThreadId();
2817 
2818  const Quantum
2819  *magick_restrict p;
2820 
2821  Quantum
2822  *magick_restrict q;
2823 
2824  ssize_t
2825  x;
2826 
2827  ssize_t
2828  center;
2829 
2830  if (status == MagickFalse)
2831  continue;
2832  p=GetCacheViewVirtualPixels(image_view,-offset.x,y-offset.y,width,
2833  kernel->height,exception);
2834  q=GetCacheViewAuthenticPixels(morphology_view,0,y,morphology_image->columns,
2835  1,exception);
2836  if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
2837  {
2838  status=MagickFalse;
2839  continue;
2840  }
2841  center=(ssize_t) (GetPixelChannels(image)*width*offset.y+
2842  GetPixelChannels(image)*offset.x);
2843  for (x=0; x < (ssize_t) image->columns; x++)
2844  {
2845  ssize_t
2846  i;
2847 
2848  for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
2849  {
2850  double
2851  alpha,
2852  gamma,
2853  intensity,
2854  maximum,
2855  minimum,
2856  pixel;
2857 
2858  PixelChannel
2859  channel;
2860 
2861  PixelTrait
2862  morphology_traits,
2863  traits;
2864 
2865  const MagickRealType
2866  *magick_restrict k;
2867 
2868  const Quantum
2869  *magick_restrict pixels,
2870  *magick_restrict quantum_pixels;
2871 
2872  ssize_t
2873  u;
2874 
2875  size_t
2876  count;
2877 
2878  ssize_t
2879  v;
2880 
2881  channel=GetPixelChannelChannel(image,i);
2882  traits=GetPixelChannelTraits(image,channel);
2883  morphology_traits=GetPixelChannelTraits(morphology_image,channel);
2884  if ((traits == UndefinedPixelTrait) ||
2885  (morphology_traits == UndefinedPixelTrait))
2886  continue;
2887  if ((traits & CopyPixelTrait) != 0)
2888  {
2889  SetPixelChannel(morphology_image,channel,p[center+i],q);
2890  continue;
2891  }
2892  pixels=p;
2893  quantum_pixels=(const Quantum *) NULL;
2894  maximum=0.0;
2895  minimum=(double) QuantumRange;
2896  switch (method)
2897  {
2898  case ConvolveMorphology:
2899  {
2900  pixel=bias;
2901  break;
2902  }
2903  case DilateMorphology:
2904  case ErodeIntensityMorphology:
2905  {
2906  pixel=0.0;
2907  break;
2908  }
2909  default:
2910  {
2911  pixel=(double) p[center+i];
2912  break;
2913  }
2914  }
2915  count=0;
2916  gamma=1.0;
2917  switch (method)
2918  {
2919  case ConvolveMorphology:
2920  {
2921  /*
2922  Weighted Average of pixels using reflected kernel
2923 
2924  For correct working of this operation for asymetrical kernels,
2925  the kernel needs to be applied in its reflected form. That is
2926  its values needs to be reversed.
2927 
2928  Correlation is actually the same as this but without reflecting
2929  the kernel, and thus 'lower-level' that Convolution. However as
2930  Convolution is the more common method used, and it does not
2931  really cost us much in terms of processing to use a reflected
2932  kernel, so it is Convolution that is implemented.
2933 
2934  Correlation will have its kernel reflected before calling this
2935  function to do a Convolve.
2936 
2937  For more details of Correlation vs Convolution see
2938  http://www.cs.umd.edu/~djacobs/CMSC426/Convolution.pdf
2939  */
2940  k=(&kernel->values[kernel->width*kernel->height-1]);
2941  if (((image->alpha_trait & BlendPixelTrait) == 0) ||
2942  ((morphology_traits & BlendPixelTrait) == 0))
2943  {
2944  /*
2945  No alpha blending.
2946  */
2947  for (v=0; v < (ssize_t) kernel->height; v++)
2948  {
2949  for (u=0; u < (ssize_t) kernel->width; u++)
2950  {
2951  if (!IsNaN(*k))
2952  {
2953  pixel+=(*k)*pixels[i];
2954  count++;
2955  }
2956  k--;
2957  pixels+=GetPixelChannels(image);
2958  }
2959  pixels+=(image->columns-1)*GetPixelChannels(image);
2960  }
2961  break;
2962  }
2963  /*
2964  Alpha blending.
2965  */
2966  gamma=0.0;
2967  for (v=0; v < (ssize_t) kernel->height; v++)
2968  {
2969  for (u=0; u < (ssize_t) kernel->width; u++)
2970  {
2971  if (!IsNaN(*k))
2972  {
2973  alpha=(double) (QuantumScale*GetPixelAlpha(image,pixels));
2974  pixel+=alpha*(*k)*pixels[i];
2975  gamma+=alpha*(*k);
2976  count++;
2977  }
2978  k--;
2979  pixels+=GetPixelChannels(image);
2980  }
2981  pixels+=(image->columns-1)*GetPixelChannels(image);
2982  }
2983  break;
2984  }
2985  case ErodeMorphology:
2986  {
2987  /*
2988  Minimum value within kernel neighbourhood.
2989 
2990  The kernel is not reflected for this operation. In normal
2991  Greyscale Morphology, the kernel value should be added
2992  to the real value, this is currently not done, due to the
2993  nature of the boolean kernels being used.
2994  */
2995  k=kernel->values;
2996  for (v=0; v < (ssize_t) kernel->height; v++)
2997  {
2998  for (u=0; u < (ssize_t) kernel->width; u++)
2999  {
3000  if (!IsNaN(*k) && (*k >= 0.5))
3001  {
3002  if ((double) pixels[i] < pixel)
3003  pixel=(double) pixels[i];
3004  }
3005  k++;
3006  pixels+=GetPixelChannels(image);
3007  }
3008  pixels+=(image->columns-1)*GetPixelChannels(image);
3009  }
3010  break;
3011  }
3012  case DilateMorphology:
3013  {
3014  /*
3015  Maximum value within kernel neighbourhood.
3016 
3017  For correct working of this operation for asymetrical kernels,
3018  the kernel needs to be applied in its reflected form. That is
3019  its values needs to be reversed.
3020 
3021  In normal Greyscale Morphology, the kernel value should be
3022  added to the real value, this is currently not done, due to the
3023  nature of the boolean kernels being used.
3024  */
3025  k=(&kernel->values[kernel->width*kernel->height-1]);
3026  for (v=0; v < (ssize_t) kernel->height; v++)
3027  {
3028  for (u=0; u < (ssize_t) kernel->width; u++)
3029  {
3030  if (!IsNaN(*k) && (*k > 0.5))
3031  {
3032  if ((double) pixels[i] > pixel)
3033  pixel=(double) pixels[i];
3034  }
3035  k--;
3036  pixels+=GetPixelChannels(image);
3037  }
3038  pixels+=(image->columns-1)*GetPixelChannels(image);
3039  }
3040  break;
3041  }
3042  case HitAndMissMorphology:
3043  case ThinningMorphology:
3044  case ThickenMorphology:
3045  {
3046  /*
3047  Minimum of foreground pixel minus maxumum of background pixels.
3048 
3049  The kernel is not reflected for this operation, and consists
3050  of both foreground and background pixel neighbourhoods, 0.0 for
3051  background, and 1.0 for foreground with either Nan or 0.5 values
3052  for don't care.
3053 
3054  This never produces a meaningless negative result. Such results
3055  cause Thinning/Thicken to not work correctly when used against a
3056  greyscale image.
3057  */
3058  k=kernel->values;
3059  for (v=0; v < (ssize_t) kernel->height; v++)
3060  {
3061  for (u=0; u < (ssize_t) kernel->width; u++)
3062  {
3063  if (!IsNaN(*k))
3064  {
3065  if (*k > 0.7)
3066  {
3067  if ((double) pixels[i] < minimum)
3068  minimum=(double) pixels[i];
3069  }
3070  else
3071  if (*k < 0.3)
3072  {
3073  if ((double) pixels[i] > maximum)
3074  maximum=(double) pixels[i];
3075  }
3076  count++;
3077  }
3078  k++;
3079  pixels+=GetPixelChannels(image);
3080  }
3081  pixels+=(image->columns-1)*GetPixelChannels(image);
3082  }
3083  minimum-=maximum;
3084  if (minimum < 0.0)
3085  minimum=0.0;
3086  pixel=minimum;
3087  if (method == ThinningMorphology)
3088  pixel=(double) p[center+i]-minimum;
3089  else
3090  if (method == ThickenMorphology)
3091  pixel=(double) p[center+i]+minimum;
3092  break;
3093  }
3094  case ErodeIntensityMorphology:
3095  {
3096  /*
3097  Select pixel with minimum intensity within kernel neighbourhood.
3098 
3099  The kernel is not reflected for this operation.
3100  */
3101  k=kernel->values;
3102  for (v=0; v < (ssize_t) kernel->height; v++)
3103  {
3104  for (u=0; u < (ssize_t) kernel->width; u++)
3105  {
3106  if (!IsNaN(*k) && (*k >= 0.5))
3107  {
3108  intensity=(double) GetPixelIntensity(image,pixels);
3109  if (intensity < minimum)
3110  {
3111  quantum_pixels=pixels;
3112  pixel=(double) pixels[i];
3113  minimum=intensity;
3114  }
3115  count++;
3116  }
3117  k++;
3118  pixels+=GetPixelChannels(image);
3119  }
3120  pixels+=(image->columns-1)*GetPixelChannels(image);
3121  }
3122  break;
3123  }
3124  case DilateIntensityMorphology:
3125  {
3126  /*
3127  Select pixel with maximum intensity within kernel neighbourhood.
3128 
3129  The kernel is not reflected for this operation.
3130  */
3131  k=(&kernel->values[kernel->width*kernel->height-1]);
3132  for (v=0; v < (ssize_t) kernel->height; v++)
3133  {
3134  for (u=0; u < (ssize_t) kernel->width; u++)
3135  {
3136  if (!IsNaN(*k) && (*k >= 0.5))
3137  {
3138  intensity=(double) GetPixelIntensity(image,pixels);
3139  if (intensity > maximum)
3140  {
3141  pixel=(double) pixels[i];
3142  quantum_pixels=pixels;
3143  maximum=intensity;
3144  }
3145  count++;
3146  }
3147  k--;
3148  pixels+=GetPixelChannels(image);
3149  }
3150  pixels+=(image->columns-1)*GetPixelChannels(image);
3151  }
3152  break;
3153  }
3154  case IterativeDistanceMorphology:
3155  {
3156  /*
3157  Compute th iterative distance from black edge of a white image
3158  shape. Essentially white values are decreased to the smallest
3159  'distance from edge' it can find.
3160 
3161  It works by adding kernel values to the neighbourhood, and
3162  select the minimum value found. The kernel is rotated before
3163  use, so kernel distances match resulting distances, when a user
3164  provided asymmetric kernel is applied.
3165 
3166  This code is nearly identical to True GrayScale Morphology but
3167  not quite.
3168 
3169  GreyDilate Kernel values added, maximum value found Kernel is
3170  rotated before use.
3171 
3172  GrayErode: Kernel values subtracted and minimum value found No
3173  kernel rotation used.
3174 
3175  Note the Iterative Distance method is essentially a
3176  GrayErode, but with negative kernel values, and kernel rotation
3177  applied.
3178  */
3179  k=(&kernel->values[kernel->width*kernel->height-1]);
3180  for (v=0; v < (ssize_t) kernel->height; v++)
3181  {
3182  for (u=0; u < (ssize_t) kernel->width; u++)
3183  {
3184  if (!IsNaN(*k))
3185  {
3186  if ((pixels[i]+(*k)) < pixel)
3187  pixel=(double) pixels[i]+(*k);
3188  count++;
3189  }
3190  k--;
3191  pixels+=GetPixelChannels(image);
3192  }
3193  pixels+=(image->columns-1)*GetPixelChannels(image);
3194  }
3195  break;
3196  }
3197  case UndefinedMorphology:
3198  default:
3199  break;
3200  }
3201  if (quantum_pixels != (const Quantum *) NULL)
3202  {
3203  SetPixelChannel(morphology_image,channel,quantum_pixels[i],q);
3204  continue;
3205  }
3206  gamma=PerceptibleReciprocal(gamma);
3207  SetPixelChannel(morphology_image,channel,ClampToQuantum(gamma*pixel),q);
3208  if (fabs(pixel-p[center+i]) >= MagickEpsilon)
3209  changes[id]++;
3210  }
3211  p+=GetPixelChannels(image);
3212  q+=GetPixelChannels(morphology_image);
3213  }
3214  if (SyncCacheViewAuthenticPixels(morphology_view,exception) == MagickFalse)
3215  status=MagickFalse;
3216  if (image->progress_monitor != (MagickProgressMonitor) NULL)
3217  {
3218  MagickBooleanType
3219  proceed;
3220 
3221 #if defined(MAGICKCORE_OPENMP_SUPPORT)
3222  #pragma omp atomic
3223 #endif
3224  progress++;
3225  proceed=SetImageProgress(image,MorphologyTag,progress,image->rows);
3226  if (proceed == MagickFalse)
3227  status=MagickFalse;
3228  }
3229  }
3230  morphology_view=DestroyCacheView(morphology_view);
3231  image_view=DestroyCacheView(image_view);
3232  for (j=0; j < (ssize_t) GetOpenMPMaximumThreads(); j++)
3233  changed+=changes[j];
3234  changes=(size_t *) RelinquishMagickMemory(changes);
3235  return(status ? (ssize_t) changed/GetImageChannels(image) : -1);
3236 }
3237 
3238 /*
3239  This is almost identical to the MorphologyPrimative() function above, but
3240  applies the primitive directly to the actual image using two passes, once in
3241  each direction, with the results of the previous (and current) row being
3242  re-used.
3243 
3244  That is after each row is 'Sync'ed' into the image, the next row makes use of
3245  those values as part of the calculation of the next row. It repeats, but
3246  going in the oppisite (bottom-up) direction.
3247 
3248  Because of this 're-use of results' this function can not make use of multi-
3249  threaded, parellel processing.
3250 */
3251 static ssize_t MorphologyPrimitiveDirect(Image *image,
3252  const MorphologyMethod method,const KernelInfo *kernel,
3253  ExceptionInfo *exception)
3254 {
3255  CacheView
3256  *morphology_view,
3257  *image_view;
3258 
3259  MagickBooleanType
3260  status;
3261 
3262  MagickOffsetType
3263  progress;
3264 
3265  OffsetInfo
3266  offset;
3267 
3268  size_t
3269  width,
3270  changed;
3271 
3272  ssize_t
3273  y;
3274 
3275  assert(image != (Image *) NULL);
3276  assert(image->signature == MagickCoreSignature);
3277  assert(kernel != (KernelInfo *) NULL);
3278  assert(kernel->signature == MagickCoreSignature);
3279  assert(exception != (ExceptionInfo *) NULL);
3280  assert(exception->signature == MagickCoreSignature);
3281  status=MagickTrue;
3282  changed=0;
3283  progress=0;
3284  switch(method)
3285  {
3286  case DistanceMorphology:
3287  case VoronoiMorphology:
3288  {
3289  /*
3290  Kernel reflected about origin.
3291  */
3292  offset.x=(ssize_t) kernel->width-kernel->x-1;
3293  offset.y=(ssize_t) kernel->height-kernel->y-1;
3294  break;
3295  }
3296  default:
3297  {
3298  offset.x=kernel->x;
3299  offset.y=kernel->y;
3300  break;
3301  }
3302  }
3303  /*
3304  Two views into same image, do not thread.
3305  */
3306  image_view=AcquireVirtualCacheView(image,exception);
3307  morphology_view=AcquireAuthenticCacheView(image,exception);
3308  width=image->columns+kernel->width-1;
3309  for (y=0; y < (ssize_t) image->rows; y++)
3310  {
3311  const Quantum
3312  *magick_restrict p;
3313 
3314  Quantum
3315  *magick_restrict q;
3316 
3317  ssize_t
3318  x;
3319 
3320  /*
3321  Read virtual pixels, and authentic pixels, from the same image! We read
3322  using virtual to get virtual pixel handling, but write back into the same
3323  image.
3324 
3325  Only top half of kernel is processed as we do a single pass downward
3326  through the image iterating the distance function as we go.
3327  */
3328  if (status == MagickFalse)
3329  continue;
3330  p=GetCacheViewVirtualPixels(image_view,-offset.x,y-offset.y,width,(size_t)
3331  offset.y+1,exception);
3332  q=GetCacheViewAuthenticPixels(morphology_view,0,y,image->columns,1,
3333  exception);
3334  if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
3335  {
3336  status=MagickFalse;
3337  continue;
3338  }
3339  for (x=0; x < (ssize_t) image->columns; x++)
3340  {
3341  ssize_t
3342  i;
3343 
3344  for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
3345  {
3346  double
3347  pixel;
3348 
3349  PixelChannel
3350  channel;
3351 
3352  PixelTrait
3353  traits;
3354 
3355  const MagickRealType
3356  *magick_restrict k;
3357 
3358  const Quantum
3359  *magick_restrict pixels;
3360 
3361  ssize_t
3362  u;
3363 
3364  ssize_t
3365  v;
3366 
3367  channel=GetPixelChannelChannel(image,i);
3368  traits=GetPixelChannelTraits(image,channel);
3369  if (traits == UndefinedPixelTrait)
3370  continue;
3371  if ((traits & CopyPixelTrait) != 0)
3372  continue;
3373  pixels=p;
3374  pixel=(double) QuantumRange;
3375  switch (method)
3376  {
3377  case DistanceMorphology:
3378  {
3379  k=(&kernel->values[kernel->width*kernel->height-1]);
3380  for (v=0; v <= offset.y; v++)
3381  {
3382  for (u=0; u < (ssize_t) kernel->width; u++)
3383  {
3384  if (!IsNaN(*k))
3385  {
3386  if ((pixels[i]+(*k)) < pixel)
3387  pixel=(double) pixels[i]+(*k);
3388  }
3389  k--;
3390  pixels+=GetPixelChannels(image);
3391  }
3392  pixels+=(image->columns-1)*GetPixelChannels(image);
3393  }
3394  k=(&kernel->values[kernel->width*(kernel->y+1)-1]);
3395  pixels=q-offset.x*GetPixelChannels(image);
3396  for (u=0; u < offset.x; u++)
3397  {
3398  if (!IsNaN(*k) && ((x+u-offset.x) >= 0))
3399  {
3400  if ((pixels[i]+(*k)) < pixel)
3401  pixel=(double) pixels[i]+(*k);
3402  }
3403  k--;
3404  pixels+=GetPixelChannels(image);
3405  }
3406  break;
3407  }
3408  case VoronoiMorphology:
3409  {
3410  k=(&kernel->values[kernel->width*kernel->height-1]);
3411  for (v=0; v < offset.y; v++)
3412  {
3413  for (u=0; u < (ssize_t) kernel->width; u++)
3414  {
3415  if (!IsNaN(*k))
3416  {
3417  if ((pixels[i]+(*k)) < pixel)
3418  pixel=(double) pixels[i]+(*k);
3419  }
3420  k--;
3421  pixels+=GetPixelChannels(image);
3422  }
3423  pixels+=(image->columns-1)*GetPixelChannels(image);
3424  }
3425  k=(&kernel->values[kernel->width*(kernel->y+1)-1]);
3426  pixels=q-offset.x*GetPixelChannels(image);
3427  for (u=0; u < offset.x; u++)
3428  {
3429  if (!IsNaN(*k) && ((x+u-offset.x) >= 0))
3430  {
3431  if ((pixels[i]+(*k)) < pixel)
3432  pixel=(double) pixels[i]+(*k);
3433  }
3434  k--;
3435  pixels+=GetPixelChannels(image);
3436  }
3437  break;
3438  }
3439  default:
3440  break;
3441  }
3442  if (fabs(pixel-q[i]) > MagickEpsilon)
3443  changed++;
3444  q[i]=ClampToQuantum(pixel);
3445  }
3446  p+=GetPixelChannels(image);
3447  q+=GetPixelChannels(image);
3448  }
3449  if (SyncCacheViewAuthenticPixels(morphology_view,exception) == MagickFalse)
3450  status=MagickFalse;
3451  if (image->progress_monitor != (MagickProgressMonitor) NULL)
3452  {
3453  MagickBooleanType
3454  proceed;
3455 
3456 #if defined(MAGICKCORE_OPENMP_SUPPORT)
3457  #pragma omp atomic
3458 #endif
3459  progress++;
3460  proceed=SetImageProgress(image,MorphologyTag,progress,2*image->rows);
3461  if (proceed == MagickFalse)
3462  status=MagickFalse;
3463  }
3464  }
3465  morphology_view=DestroyCacheView(morphology_view);
3466  image_view=DestroyCacheView(image_view);
3467  /*
3468  Do the reverse pass through the image.
3469  */
3470  image_view=AcquireVirtualCacheView(image,exception);
3471  morphology_view=AcquireAuthenticCacheView(image,exception);
3472  for (y=(ssize_t) image->rows-1; y >= 0; y--)
3473  {
3474  const Quantum
3475  *magick_restrict p;
3476 
3477  Quantum
3478  *magick_restrict q;
3479 
3480  ssize_t
3481  x;
3482 
3483  /*
3484  Read virtual pixels, and authentic pixels, from the same image. We
3485  read using virtual to get virtual pixel handling, but write back
3486  into the same image.
3487 
3488  Only the bottom half of the kernel is processed as we up the image.
3489  */
3490  if (status == MagickFalse)
3491  continue;
3492  p=GetCacheViewVirtualPixels(image_view,-offset.x,y,width,(size_t)
3493  kernel->y+1,exception);
3494  q=GetCacheViewAuthenticPixels(morphology_view,0,y,image->columns,1,
3495  exception);
3496  if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
3497  {
3498  status=MagickFalse;
3499  continue;
3500  }
3501  p+=(image->columns-1)*GetPixelChannels(image);
3502  q+=(image->columns-1)*GetPixelChannels(image);
3503  for (x=(ssize_t) image->columns-1; x >= 0; x--)
3504  {
3505  ssize_t
3506  i;
3507 
3508  for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
3509  {
3510  double
3511  pixel;
3512 
3513  PixelChannel
3514  channel;
3515 
3516  PixelTrait
3517  traits;
3518 
3519  const MagickRealType
3520  *magick_restrict k;
3521 
3522  const Quantum
3523  *magick_restrict pixels;
3524 
3525  ssize_t
3526  u;
3527 
3528  ssize_t
3529  v;
3530 
3531  channel=GetPixelChannelChannel(image,i);
3532  traits=GetPixelChannelTraits(image,channel);
3533  if (traits == UndefinedPixelTrait)
3534  continue;
3535  if ((traits & CopyPixelTrait) != 0)
3536  continue;
3537  pixels=p;
3538  pixel=(double) QuantumRange;
3539  switch (method)
3540  {
3541  case DistanceMorphology:
3542  {
3543  k=(&kernel->values[kernel->width*(kernel->y+1)-1]);
3544  for (v=offset.y; v < (ssize_t) kernel->height; v++)
3545  {
3546  for (u=0; u < (ssize_t) kernel->width; u++)
3547  {
3548  if (!IsNaN(*k))
3549  {
3550  if ((pixels[i]+(*k)) < pixel)
3551  pixel=(double) pixels[i]+(*k);
3552  }
3553  k--;
3554  pixels+=GetPixelChannels(image);
3555  }
3556  pixels+=(image->columns-1)*GetPixelChannels(image);
3557  }
3558  k=(&kernel->values[kernel->width*kernel->y+kernel->x-1]);
3559  pixels=q;
3560  for (u=offset.x+1; u < (ssize_t) kernel->width; u++)
3561  {
3562  pixels+=GetPixelChannels(image);
3563  if (!IsNaN(*k) && ((x+u-offset.x) < (ssize_t) image->columns))
3564  {
3565  if ((pixels[i]+(*k)) < pixel)
3566  pixel=(double) pixels[i]+(*k);
3567  }
3568  k--;
3569  }
3570  break;
3571  }
3572  case VoronoiMorphology:
3573  {
3574  k=(&kernel->values[kernel->width*(kernel->y+1)-1]);
3575  for (v=offset.y; v < (ssize_t) kernel->height; v++)
3576  {
3577  for (u=0; u < (ssize_t) kernel->width; u++)
3578  {
3579  if (!IsNaN(*k))
3580  {
3581  if ((pixels[i]+(*k)) < pixel)
3582  pixel=(double) pixels[i]+(*k);
3583  }
3584  k--;
3585  pixels+=GetPixelChannels(image);
3586  }
3587  pixels+=(image->columns-1)*GetPixelChannels(image);
3588  }
3589  k=(&kernel->values[kernel->width*(kernel->y+1)-1]);
3590  pixels=q;
3591  for (u=offset.x+1; u < (ssize_t) kernel->width; u++)
3592  {
3593  pixels+=GetPixelChannels(image);
3594  if (!IsNaN(*k) && ((x+u-offset.x) < (ssize_t) image->columns))
3595  {
3596  if ((pixels[i]+(*k)) < pixel)
3597  pixel=(double) pixels[i]+(*k);
3598  }
3599  k--;
3600  }
3601  break;
3602  }
3603  default:
3604  break;
3605  }
3606  if (fabs(pixel-q[i]) > MagickEpsilon)
3607  changed++;
3608  q[i]=ClampToQuantum(pixel);
3609  }
3610  p-=GetPixelChannels(image);
3611  q-=GetPixelChannels(image);
3612  }
3613  if (SyncCacheViewAuthenticPixels(morphology_view,exception) == MagickFalse)
3614  status=MagickFalse;
3615  if (image->progress_monitor != (MagickProgressMonitor) NULL)
3616  {
3617  MagickBooleanType
3618  proceed;
3619 
3620 #if defined(MAGICKCORE_OPENMP_SUPPORT)
3621  #pragma omp atomic
3622 #endif
3623  progress++;
3624  proceed=SetImageProgress(image,MorphologyTag,progress,2*image->rows);
3625  if (proceed == MagickFalse)
3626  status=MagickFalse;
3627  }
3628  }
3629  morphology_view=DestroyCacheView(morphology_view);
3630  image_view=DestroyCacheView(image_view);
3631  return(status ? (ssize_t) changed/GetImageChannels(image) : -1);
3632 }
3633 
3634 /*
3635  Apply a Morphology by calling one of the above low level primitive
3636  application functions. This function handles any iteration loops,
3637  composition or re-iteration of results, and compound morphology methods that
3638  is based on multiple low-level (staged) morphology methods.
3639 
3640  Basically this provides the complex glue between the requested morphology
3641  method and raw low-level implementation (above).
3642 */
3643 MagickPrivate Image *MorphologyApply(const Image *image,
3644  const MorphologyMethod method, const ssize_t iterations,
3645  const KernelInfo *kernel, const CompositeOperator compose,const double bias,
3646  ExceptionInfo *exception)
3647 {
3648  CompositeOperator
3649  curr_compose;
3650 
3651  Image
3652  *curr_image, /* Image we are working with or iterating */
3653  *work_image, /* secondary image for primitive iteration */
3654  *save_image, /* saved image - for 'edge' method only */
3655  *rslt_image; /* resultant image - after multi-kernel handling */
3656 
3657  KernelInfo
3658  *reflected_kernel, /* A reflected copy of the kernel (if needed) */
3659  *norm_kernel, /* the current normal un-reflected kernel */
3660  *rflt_kernel, /* the current reflected kernel (if needed) */
3661  *this_kernel; /* the kernel being applied */
3662 
3663  MorphologyMethod
3664  primitive; /* the current morphology primitive being applied */
3665 
3666  CompositeOperator
3667  rslt_compose; /* multi-kernel compose method for results to use */
3668 
3669  MagickBooleanType
3670  special, /* do we use a direct modify function? */
3671  verbose; /* verbose output of results */
3672 
3673  size_t
3674  method_loop, /* Loop 1: number of compound method iterations (norm 1) */
3675  method_limit, /* maximum number of compound method iterations */
3676  kernel_number, /* Loop 2: the kernel number being applied */
3677  stage_loop, /* Loop 3: primitive loop for compound morphology */
3678  stage_limit, /* how many primitives are in this compound */
3679  kernel_loop, /* Loop 4: iterate the kernel over image */
3680  kernel_limit, /* number of times to iterate kernel */
3681  count, /* total count of primitive steps applied */
3682  kernel_changed, /* total count of changed using iterated kernel */
3683  method_changed; /* total count of changed over method iteration */
3684 
3685  ssize_t
3686  changed; /* number pixels changed by last primitive operation */
3687 
3688  char
3689  v_info[MagickPathExtent];
3690 
3691  assert(image != (Image *) NULL);
3692  assert(image->signature == MagickCoreSignature);
3693  assert(kernel != (KernelInfo *) NULL);
3694  assert(kernel->signature == MagickCoreSignature);
3695  assert(exception != (ExceptionInfo *) NULL);
3696  assert(exception->signature == MagickCoreSignature);
3697 
3698  count = 0; /* number of low-level morphology primitives performed */
3699  if ( iterations == 0 )
3700  return((Image *) NULL); /* null operation - nothing to do! */
3701 
3702  kernel_limit = (size_t) iterations;
3703  if ( iterations < 0 ) /* negative interations = infinite (well alomst) */
3704  kernel_limit = image->columns>image->rows ? image->columns : image->rows;
3705 
3706  verbose = IsStringTrue(GetImageArtifact(image,"debug"));
3707 
3708  /* initialise for cleanup */
3709  curr_image = (Image *) image;
3710  curr_compose = image->compose;
3711  (void) curr_compose;
3712  work_image = save_image = rslt_image = (Image *) NULL;
3713  reflected_kernel = (KernelInfo *) NULL;
3714 
3715  /* Initialize specific methods
3716  * + which loop should use the given iteratations
3717  * + how many primitives make up the compound morphology
3718  * + multi-kernel compose method to use (by default)
3719  */
3720  method_limit = 1; /* just do method once, unless otherwise set */
3721  stage_limit = 1; /* assume method is not a compound */
3722  special = MagickFalse; /* assume it is NOT a direct modify primitive */
3723  rslt_compose = compose; /* and we are composing multi-kernels as given */
3724  switch( method ) {
3725  case SmoothMorphology: /* 4 primitive compound morphology */
3726  stage_limit = 4;
3727  break;
3728  case OpenMorphology: /* 2 primitive compound morphology */
3729  case OpenIntensityMorphology:
3730  case TopHatMorphology:
3731  case CloseMorphology:
3732  case CloseIntensityMorphology:
3733  case BottomHatMorphology:
3734  case EdgeMorphology:
3735  stage_limit = 2;
3736  break;
3737  case HitAndMissMorphology:
3738  rslt_compose = LightenCompositeOp; /* Union of multi-kernel results */
3739  /* FALL THUR */
3740  case ThinningMorphology:
3741  case ThickenMorphology:
3742  method_limit = kernel_limit; /* iterate the whole method */
3743  kernel_limit = 1; /* do not do kernel iteration */
3744  break;
3745  case DistanceMorphology:
3746  case VoronoiMorphology:
3747  special = MagickTrue; /* use special direct primative */
3748  break;
3749  default:
3750  break;
3751  }
3752 
3753  /* Apply special methods with special requirments
3754  ** For example, single run only, or post-processing requirements
3755  */
3756  if ( special != MagickFalse )
3757  {
3758  rslt_image=CloneImage(image,0,0,MagickTrue,exception);
3759  if (rslt_image == (Image *) NULL)
3760  goto error_cleanup;
3761  if (SetImageStorageClass(rslt_image,DirectClass,exception) == MagickFalse)
3762  goto error_cleanup;
3763 
3764  changed=MorphologyPrimitiveDirect(rslt_image,method,kernel,exception);
3765 
3766  if (verbose != MagickFalse)
3767  (void) (void) FormatLocaleFile(stderr,
3768  "%s:%.20g.%.20g #%.20g => Changed %.20g\n",
3769  CommandOptionToMnemonic(MagickMorphologyOptions, method),
3770  1.0,0.0,1.0, (double) changed);
3771 
3772  if ( changed < 0 )
3773  goto error_cleanup;
3774 
3775  if ( method == VoronoiMorphology ) {
3776  /* Preserve the alpha channel of input image - but turned it off */
3777  (void) SetImageAlphaChannel(rslt_image, DeactivateAlphaChannel,
3778  exception);
3779  (void) CompositeImage(rslt_image,image,CopyAlphaCompositeOp,
3780  MagickTrue,0,0,exception);
3781  (void) SetImageAlphaChannel(rslt_image, DeactivateAlphaChannel,
3782  exception);
3783  }
3784  goto exit_cleanup;
3785  }
3786 
3787  /* Handle user (caller) specified multi-kernel composition method */
3788  if ( compose != UndefinedCompositeOp )
3789  rslt_compose = compose; /* override default composition for method */
3790  if ( rslt_compose == UndefinedCompositeOp )
3791  rslt_compose = NoCompositeOp; /* still not defined! Then re-iterate */
3792 
3793  /* Some methods require a reflected kernel to use with primitives.
3794  * Create the reflected kernel for those methods. */
3795  switch ( method ) {
3796  case CorrelateMorphology:
3797  case CloseMorphology:
3798  case CloseIntensityMorphology:
3799  case BottomHatMorphology:
3800  case SmoothMorphology:
3801  reflected_kernel = CloneKernelInfo(kernel);
3802  if (reflected_kernel == (KernelInfo *) NULL)
3803  goto error_cleanup;
3804  RotateKernelInfo(reflected_kernel,180);
3805  break;
3806  default:
3807  break;
3808  }
3809 
3810  /* Loops around more primitive morpholgy methods
3811  ** erose, dilate, open, close, smooth, edge, etc...
3812  */
3813  /* Loop 1: iterate the compound method */
3814  method_loop = 0;
3815  method_changed = 1;
3816  while ( method_loop < method_limit && method_changed > 0 ) {
3817  method_loop++;
3818  method_changed = 0;
3819 
3820  /* Loop 2: iterate over each kernel in a multi-kernel list */
3821  norm_kernel = (KernelInfo *) kernel;
3822  this_kernel = (KernelInfo *) kernel;
3823  rflt_kernel = reflected_kernel;
3824 
3825  kernel_number = 0;
3826  while ( norm_kernel != NULL ) {
3827 
3828  /* Loop 3: Compound Morphology Staging - Select Primative to apply */
3829  stage_loop = 0; /* the compound morphology stage number */
3830  while ( stage_loop < stage_limit ) {
3831  stage_loop++; /* The stage of the compound morphology */
3832 
3833  /* Select primitive morphology for this stage of compound method */
3834  this_kernel = norm_kernel; /* default use unreflected kernel */
3835  primitive = method; /* Assume method is a primitive */
3836  switch( method ) {
3837  case ErodeMorphology: /* just erode */
3838  case EdgeInMorphology: /* erode and image difference */
3839  primitive = ErodeMorphology;
3840  break;
3841  case DilateMorphology: /* just dilate */
3842  case EdgeOutMorphology: /* dilate and image difference */
3843  primitive = DilateMorphology;
3844  break;
3845  case OpenMorphology: /* erode then dialate */
3846  case TopHatMorphology: /* open and image difference */
3847  primitive = ErodeMorphology;
3848  if ( stage_loop == 2 )
3849  primitive = DilateMorphology;
3850  break;
3851  case OpenIntensityMorphology:
3852  primitive = ErodeIntensityMorphology;
3853  if ( stage_loop == 2 )
3854  primitive = DilateIntensityMorphology;
3855  break;
3856  case CloseMorphology: /* dilate, then erode */
3857  case BottomHatMorphology: /* close and image difference */
3858  this_kernel = rflt_kernel; /* use the reflected kernel */
3859  primitive = DilateMorphology;
3860  if ( stage_loop == 2 )
3861  primitive = ErodeMorphology;
3862  break;
3863  case CloseIntensityMorphology:
3864  this_kernel = rflt_kernel; /* use the reflected kernel */
3865  primitive = DilateIntensityMorphology;
3866  if ( stage_loop == 2 )
3867  primitive = ErodeIntensityMorphology;
3868  break;
3869  case SmoothMorphology: /* open, close */
3870  switch ( stage_loop ) {
3871  case 1: /* start an open method, which starts with Erode */
3872  primitive = ErodeMorphology;
3873  break;
3874  case 2: /* now Dilate the Erode */
3875  primitive = DilateMorphology;
3876  break;
3877  case 3: /* Reflect kernel a close */
3878  this_kernel = rflt_kernel; /* use the reflected kernel */
3879  primitive = DilateMorphology;
3880  break;
3881  case 4: /* Finish the Close */
3882  this_kernel = rflt_kernel; /* use the reflected kernel */
3883  primitive = ErodeMorphology;
3884  break;
3885  }
3886  break;
3887  case EdgeMorphology: /* dilate and erode difference */
3888  primitive = DilateMorphology;
3889  if ( stage_loop == 2 ) {
3890  save_image = curr_image; /* save the image difference */
3891  curr_image = (Image *) image;
3892  primitive = ErodeMorphology;
3893  }
3894  break;
3895  case CorrelateMorphology:
3896  /* A Correlation is a Convolution with a reflected kernel.
3897  ** However a Convolution is a weighted sum using a reflected
3898  ** kernel. It may seem stange to convert a Correlation into a
3899  ** Convolution as the Correlation is the simplier method, but
3900  ** Convolution is much more commonly used, and it makes sense to
3901  ** implement it directly so as to avoid the need to duplicate the
3902  ** kernel when it is not required (which is typically the
3903  ** default).
3904  */
3905  this_kernel = rflt_kernel; /* use the reflected kernel */
3906  primitive = ConvolveMorphology;
3907  break;
3908  default:
3909  break;
3910  }
3911  assert( this_kernel != (KernelInfo *) NULL );
3912 
3913  /* Extra information for debugging compound operations */
3914  if (verbose != MagickFalse) {
3915  if ( stage_limit > 1 )
3916  (void) FormatLocaleString(v_info,MagickPathExtent,"%s:%.20g.%.20g -> ",
3917  CommandOptionToMnemonic(MagickMorphologyOptions,method),(double)
3918  method_loop,(double) stage_loop);
3919  else if ( primitive != method )
3920  (void) FormatLocaleString(v_info, MagickPathExtent, "%s:%.20g -> ",
3921  CommandOptionToMnemonic(MagickMorphologyOptions, method),(double)
3922  method_loop);
3923  else
3924  v_info[0] = '\0';
3925  }
3926 
3927  /* Loop 4: Iterate the kernel with primitive */
3928  kernel_loop = 0;
3929  kernel_changed = 0;
3930  changed = 1;
3931  while ( kernel_loop < kernel_limit && changed > 0 ) {
3932  kernel_loop++; /* the iteration of this kernel */
3933 
3934  /* Create a clone as the destination image, if not yet defined */
3935  if ( work_image == (Image *) NULL )
3936  {
3937  work_image=CloneImage(image,0,0,MagickTrue,exception);
3938  if (work_image == (Image *) NULL)
3939  goto error_cleanup;
3940  if (SetImageStorageClass(work_image,DirectClass,exception) == MagickFalse)
3941  goto error_cleanup;
3942  }
3943 
3944  /* APPLY THE MORPHOLOGICAL PRIMITIVE (curr -> work) */
3945  count++;
3946  changed = MorphologyPrimitive(curr_image, work_image, primitive,
3947  this_kernel, bias, exception);
3948  if (verbose != MagickFalse) {
3949  if ( kernel_loop > 1 )
3950  (void) FormatLocaleFile(stderr, "\n"); /* add end-of-line from previous */
3951  (void) (void) FormatLocaleFile(stderr,
3952  "%s%s%s:%.20g.%.20g #%.20g => Changed %.20g",
3953  v_info,CommandOptionToMnemonic(MagickMorphologyOptions,
3954  primitive),(this_kernel == rflt_kernel ) ? "*" : "",
3955  (double) (method_loop+kernel_loop-1),(double) kernel_number,
3956  (double) count,(double) changed);
3957  }
3958  if ( changed < 0 )
3959  goto error_cleanup;
3960  kernel_changed += changed;
3961  method_changed += changed;
3962 
3963  /* prepare next loop */
3964  { Image *tmp = work_image; /* swap images for iteration */
3965  work_image = curr_image;
3966  curr_image = tmp;
3967  }
3968  if ( work_image == image )
3969  work_image = (Image *) NULL; /* replace input 'image' */
3970 
3971  } /* End Loop 4: Iterate the kernel with primitive */
3972 
3973  if (verbose != MagickFalse && kernel_changed != (size_t)changed)
3974  (void) FormatLocaleFile(stderr, " Total %.20g",(double) kernel_changed);
3975  if (verbose != MagickFalse && stage_loop < stage_limit)
3976  (void) FormatLocaleFile(stderr, "\n"); /* add end-of-line before looping */
3977 
3978 #if 0
3979  (void) FormatLocaleFile(stderr, "--E-- image=0x%lx\n", (unsigned long)image);
3980  (void) FormatLocaleFile(stderr, " curr =0x%lx\n", (unsigned long)curr_image);
3981  (void) FormatLocaleFile(stderr, " work =0x%lx\n", (unsigned long)work_image);
3982  (void) FormatLocaleFile(stderr, " save =0x%lx\n", (unsigned long)save_image);
3983  (void) FormatLocaleFile(stderr, " union=0x%lx\n", (unsigned long)rslt_image);
3984 #endif
3985 
3986  } /* End Loop 3: Primative (staging) Loop for Coumpound Methods */
3987 
3988  /* Final Post-processing for some Compound Methods
3989  **
3990  ** The removal of any 'Sync' channel flag in the Image Compositon
3991  ** below ensures the methematical compose method is applied in a
3992  ** purely mathematical way, and only to the selected channels.
3993  ** Turn off SVG composition 'alpha blending'.
3994  */
3995  switch( method ) {
3996  case EdgeOutMorphology:
3997  case EdgeInMorphology:
3998  case TopHatMorphology:
3999  case BottomHatMorphology:
4000  if (verbose != MagickFalse)
4001  (void) FormatLocaleFile(stderr,
4002  "\n%s: Difference with original image",CommandOptionToMnemonic(
4003  MagickMorphologyOptions, method) );
4004  (void) CompositeImage(curr_image,image,DifferenceCompositeOp,
4005  MagickTrue,0,0,exception);
4006  break;
4007  case EdgeMorphology:
4008  if (verbose != MagickFalse)
4009  (void) FormatLocaleFile(stderr,
4010  "\n%s: Difference of Dilate and Erode",CommandOptionToMnemonic(
4011  MagickMorphologyOptions, method) );
4012  (void) CompositeImage(curr_image,save_image,DifferenceCompositeOp,
4013  MagickTrue,0,0,exception);
4014  save_image = DestroyImage(save_image); /* finished with save image */
4015  break;
4016  default:
4017  break;
4018  }
4019 
4020  /* multi-kernel handling: re-iterate, or compose results */
4021  if ( kernel->next == (KernelInfo *) NULL )
4022  rslt_image = curr_image; /* just return the resulting image */
4023  else if ( rslt_compose == NoCompositeOp )
4024  { if (verbose != MagickFalse) {
4025  if ( this_kernel->next != (KernelInfo *) NULL )
4026  (void) FormatLocaleFile(stderr, " (re-iterate)");
4027  else
4028  (void) FormatLocaleFile(stderr, " (done)");
4029  }
4030  rslt_image = curr_image; /* return result, and re-iterate */
4031  }
4032  else if ( rslt_image == (Image *) NULL)
4033  { if (verbose != MagickFalse)
4034  (void) FormatLocaleFile(stderr, " (save for compose)");
4035  rslt_image = curr_image;
4036  curr_image = (Image *) image; /* continue with original image */
4037  }
4038  else
4039  { /* Add the new 'current' result to the composition
4040  **
4041  ** The removal of any 'Sync' channel flag in the Image Compositon
4042  ** below ensures the methematical compose method is applied in a
4043  ** purely mathematical way, and only to the selected channels.
4044  ** IE: Turn off SVG composition 'alpha blending'.
4045  */
4046  if (verbose != MagickFalse)
4047  (void) FormatLocaleFile(stderr, " (compose \"%s\")",
4048  CommandOptionToMnemonic(MagickComposeOptions, rslt_compose) );
4049  (void) CompositeImage(rslt_image,curr_image,rslt_compose,MagickTrue,
4050  0,0,exception);
4051  curr_image = DestroyImage(curr_image);
4052  curr_image = (Image *) image; /* continue with original image */
4053  }
4054  if (verbose != MagickFalse)
4055  (void) FormatLocaleFile(stderr, "\n");
4056 
4057  /* loop to the next kernel in a multi-kernel list */
4058  norm_kernel = norm_kernel->next;
4059  if ( rflt_kernel != (KernelInfo *) NULL )
4060  rflt_kernel = rflt_kernel->next;
4061  kernel_number++;
4062  } /* End Loop 2: Loop over each kernel */
4063 
4064  } /* End Loop 1: compound method interation */
4065 
4066  goto exit_cleanup;
4067 
4068  /* Yes goto's are bad, but it makes cleanup lot more efficient */
4069 error_cleanup:
4070  if ( curr_image == rslt_image )
4071  curr_image = (Image *) NULL;
4072  if ( rslt_image != (Image *) NULL )
4073  rslt_image = DestroyImage(rslt_image);
4074 exit_cleanup:
4075  if ( curr_image == rslt_image || curr_image == image )
4076  curr_image = (Image *) NULL;
4077  if ( curr_image != (Image *) NULL )
4078  curr_image = DestroyImage(curr_image);
4079  if ( work_image != (Image *) NULL )
4080  work_image = DestroyImage(work_image);
4081  if ( save_image != (Image *) NULL )
4082  save_image = DestroyImage(save_image);
4083  if ( reflected_kernel != (KernelInfo *) NULL )
4084  reflected_kernel = DestroyKernelInfo(reflected_kernel);
4085  return(rslt_image);
4086 }
4087 
4088 ␌
4089 /*
4090 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4091 % %
4092 % %
4093 % %
4094 % M o r p h o l o g y I m a g e %
4095 % %
4096 % %
4097 % %
4098 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4099 %
4100 % MorphologyImage() applies a user supplied kernel to the image according to
4101 % the given mophology method.
4102 %
4103 % This function applies any and all user defined settings before calling
4104 % the above internal function MorphologyApply().
4105 %
4106 % User defined settings include...
4107 % * Output Bias for Convolution and correlation ("-define convolve:bias=??")
4108 % * Kernel Scale/normalize settings ("-define convolve:scale=??")
4109 % This can also includes the addition of a scaled unity kernel.
4110 % * Show Kernel being applied ("-define morphology:showKernel=1")
4111 %
4112 % Other operators that do not want user supplied options interfering,
4113 % especially "convolve:bias" and "morphology:showKernel" should use
4114 % MorphologyApply() directly.
4115 %
4116 % The format of the MorphologyImage method is:
4117 %
4118 % Image *MorphologyImage(const Image *image,MorphologyMethod method,
4119 % const ssize_t iterations,KernelInfo *kernel,ExceptionInfo *exception)
4120 %
4121 % A description of each parameter follows:
4122 %
4123 % o image: the image.
4124 %
4125 % o method: the morphology method to be applied.
4126 %
4127 % o iterations: apply the operation this many times (or no change).
4128 % A value of -1 means loop until no change found.
4129 % How this is applied may depend on the morphology method.
4130 % Typically this is a value of 1.
4131 %
4132 % o kernel: An array of double representing the morphology kernel.
4133 % Warning: kernel may be normalized for the Convolve method.
4134 %
4135 % o exception: return any errors or warnings in this structure.
4136 %
4137 */
4138 MagickExport Image *MorphologyImage(const Image *image,
4139  const MorphologyMethod method,const ssize_t iterations,
4140  const KernelInfo *kernel,ExceptionInfo *exception)
4141 {
4142  const char
4143  *artifact;
4144 
4145  CompositeOperator
4146  compose;
4147 
4148  double
4149  bias;
4150 
4151  Image
4152  *morphology_image;
4153 
4154  KernelInfo
4155  *curr_kernel;
4156 
4157  assert(image != (const Image *) NULL);
4158  assert(image->signature == MagickCoreSignature);
4159  assert(exception != (ExceptionInfo *) NULL);
4160  assert(exception->signature == MagickCoreSignature);
4161  if (IsEventLogging() != MagickFalse)
4162  (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
4163  curr_kernel = (KernelInfo *) kernel;
4164  bias=0.0;
4165  compose = UndefinedCompositeOp; /* use default for method */
4166 
4167  /* Apply Convolve/Correlate Normalization and Scaling Factors.
4168  * This is done BEFORE the ShowKernelInfo() function is called so that
4169  * users can see the results of the 'option:convolve:scale' option.
4170  */
4171  if ( method == ConvolveMorphology || method == CorrelateMorphology ) {
4172  /* Get the bias value as it will be needed */
4173  artifact = GetImageArtifact(image,"convolve:bias");
4174  if ( artifact != (const char *) NULL) {
4175  if (IsGeometry(artifact) == MagickFalse)
4176  (void) ThrowMagickException(exception,GetMagickModule(),
4177  OptionWarning,"InvalidSetting","'%s' '%s'",
4178  "convolve:bias",artifact);
4179  else
4180  bias=StringToDoubleInterval(artifact,(double) QuantumRange+1.0);
4181  }
4182 
4183  /* Scale kernel according to user wishes */
4184  artifact = GetImageArtifact(image,"convolve:scale");
4185  if ( artifact != (const char *) NULL ) {
4186  if (IsGeometry(artifact) == MagickFalse)
4187  (void) ThrowMagickException(exception,GetMagickModule(),
4188  OptionWarning,"InvalidSetting","'%s' '%s'",
4189  "convolve:scale",artifact);
4190  else {
4191  if ( curr_kernel == kernel )
4192  curr_kernel = CloneKernelInfo(kernel);
4193  if (curr_kernel == (KernelInfo *) NULL)
4194  return((Image *) NULL);
4195  ScaleGeometryKernelInfo(curr_kernel, artifact);
4196  }
4197  }
4198  }
4199 
4200  /* display the (normalized) kernel via stderr */
4201  artifact=GetImageArtifact(image,"morphology:showKernel");
4202  if (IsStringTrue(artifact) != MagickFalse)
4203  ShowKernelInfo(curr_kernel);
4204 
4205  /* Override the default handling of multi-kernel morphology results
4206  * If 'Undefined' use the default method
4207  * If 'None' (default for 'Convolve') re-iterate previous result
4208  * Otherwise merge resulting images using compose method given.
4209  * Default for 'HitAndMiss' is 'Lighten'.
4210  */
4211  {
4212  ssize_t
4213  parse;
4214 
4215  artifact = GetImageArtifact(image,"morphology:compose");
4216  if ( artifact != (const char *) NULL) {
4217  parse=ParseCommandOption(MagickComposeOptions,
4218  MagickFalse,artifact);
4219  if ( parse < 0 )
4220  (void) ThrowMagickException(exception,GetMagickModule(),
4221  OptionWarning,"UnrecognizedComposeOperator","'%s' '%s'",
4222  "morphology:compose",artifact);
4223  else
4224  compose=(CompositeOperator)parse;
4225  }
4226  }
4227  /* Apply the Morphology */
4228  morphology_image = MorphologyApply(image,method,iterations,
4229  curr_kernel,compose,bias,exception);
4230 
4231  /* Cleanup and Exit */
4232  if ( curr_kernel != kernel )
4233  curr_kernel=DestroyKernelInfo(curr_kernel);
4234  return(morphology_image);
4235 }
4236 ␌
4237 /*
4238 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4239 % %
4240 % %
4241 % %
4242 + R o t a t e K e r n e l I n f o %
4243 % %
4244 % %
4245 % %
4246 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4247 %
4248 % RotateKernelInfo() rotates the kernel by the angle given.
4249 %
4250 % Currently it is restricted to 90 degree angles, of either 1D kernels
4251 % or square kernels. And 'circular' rotations of 45 degrees for 3x3 kernels.
4252 % It will ignore usless rotations for specific 'named' built-in kernels.
4253 %
4254 % The format of the RotateKernelInfo method is:
4255 %
4256 % void RotateKernelInfo(KernelInfo *kernel, double angle)
4257 %
4258 % A description of each parameter follows:
4259 %
4260 % o kernel: the Morphology/Convolution kernel
4261 %
4262 % o angle: angle to rotate in degrees
4263 %
4264 % This function is currently internal to this module only, but can be exported
4265 % to other modules if needed.
4266 */
4267 static void RotateKernelInfo(KernelInfo *kernel, double angle)
4268 {
4269  /* angle the lower kernels first */
4270  if ( kernel->next != (KernelInfo *) NULL)
4271  RotateKernelInfo(kernel->next, angle);
4272 
4273  /* WARNING: Currently assumes the kernel (rightly) is horizontally symetrical
4274  **
4275  ** TODO: expand beyond simple 90 degree rotates, flips and flops
4276  */
4277 
4278  /* Modulus the angle */
4279  angle = fmod(angle, 360.0);
4280  if ( angle < 0 )
4281  angle += 360.0;
4282 
4283  if ( 337.5 < angle || angle <= 22.5 )
4284  return; /* Near zero angle - no change! - At least not at this time */
4285 
4286  /* Handle special cases */
4287  switch (kernel->type) {
4288  /* These built-in kernels are cylindrical kernels, rotating is useless */
4289  case GaussianKernel:
4290  case DoGKernel:
4291  case LoGKernel:
4292  case DiskKernel:
4293  case PeaksKernel:
4294  case LaplacianKernel:
4295  case ChebyshevKernel:
4296  case ManhattanKernel:
4297  case EuclideanKernel:
4298  return;
4299 
4300  /* These may be rotatable at non-90 angles in the future */
4301  /* but simply rotating them in multiples of 90 degrees is useless */
4302  case SquareKernel:
4303  case DiamondKernel:
4304  case PlusKernel:
4305  case CrossKernel:
4306  return;
4307 
4308  /* These only allows a +/-90 degree rotation (by transpose) */
4309  /* A 180 degree rotation is useless */
4310  case BlurKernel:
4311  if ( 135.0 < angle && angle <= 225.0 )
4312  return;
4313  if ( 225.0 < angle && angle <= 315.0 )
4314  angle -= 180;
4315  break;
4316 
4317  default:
4318  break;
4319  }
4320  /* Attempt rotations by 45 degrees -- 3x3 kernels only */
4321  if ( 22.5 < fmod(angle,90.0) && fmod(angle,90.0) <= 67.5 )
4322  {
4323  if ( kernel->width == 3 && kernel->height == 3 )
4324  { /* Rotate a 3x3 square by 45 degree angle */
4325  double t = kernel->values[0];
4326  kernel->values[0] = kernel->values[3];
4327  kernel->values[3] = kernel->values[6];
4328  kernel->values[6] = kernel->values[7];
4329  kernel->values[7] = kernel->values[8];
4330  kernel->values[8] = kernel->values[5];
4331  kernel->values[5] = kernel->values[2];
4332  kernel->values[2] = kernel->values[1];
4333  kernel->values[1] = t;
4334  /* rotate non-centered origin */
4335  if ( kernel->x != 1 || kernel->y != 1 ) {
4336  ssize_t x,y;
4337  x = (ssize_t) kernel->x-1;
4338  y = (ssize_t) kernel->y-1;
4339  if ( x == y ) x = 0;
4340  else if ( x == 0 ) x = -y;
4341  else if ( x == -y ) y = 0;
4342  else if ( y == 0 ) y = x;
4343  kernel->x = (ssize_t) x+1;
4344  kernel->y = (ssize_t) y+1;
4345  }
4346  angle = fmod(angle+315.0, 360.0); /* angle reduced 45 degrees */
4347  kernel->angle = fmod(kernel->angle+45.0, 360.0);
4348  }
4349  else
4350  perror("Unable to rotate non-3x3 kernel by 45 degrees");
4351  }
4352  if ( 45.0 < fmod(angle, 180.0) && fmod(angle,180.0) <= 135.0 )
4353  {
4354  if ( kernel->width == 1 || kernel->height == 1 )
4355  { /* Do a transpose of a 1 dimensional kernel,
4356  ** which results in a fast 90 degree rotation of some type.
4357  */
4358  ssize_t
4359  t;
4360  t = (ssize_t) kernel->width;
4361  kernel->width = kernel->height;
4362  kernel->height = (size_t) t;
4363  t = kernel->x;
4364  kernel->x = kernel->y;
4365  kernel->y = t;
4366  if ( kernel->width == 1 ) {
4367  angle = fmod(angle+270.0, 360.0); /* angle reduced 90 degrees */
4368  kernel->angle = fmod(kernel->angle+90.0, 360.0);
4369  } else {
4370  angle = fmod(angle+90.0, 360.0); /* angle increased 90 degrees */
4371  kernel->angle = fmod(kernel->angle+270.0, 360.0);
4372  }
4373  }
4374  else if ( kernel->width == kernel->height )
4375  { /* Rotate a square array of values by 90 degrees */
4376  { ssize_t
4377  i,j,x,y;
4378 
4379  MagickRealType
4380  *k,t;
4381 
4382  k=kernel->values;
4383  for( i=0, x=(ssize_t) kernel->width-1; i<=x; i++, x--)
4384  for( j=0, y=(ssize_t) kernel->height-1; j<y; j++, y--)
4385  { t = k[i+j*kernel->width];
4386  k[i+j*kernel->width] = k[j+x*kernel->width];
4387  k[j+x*kernel->width] = k[x+y*kernel->width];
4388  k[x+y*kernel->width] = k[y+i*kernel->width];
4389  k[y+i*kernel->width] = t;
4390  }
4391  }
4392  /* rotate the origin - relative to center of array */
4393  { ssize_t x,y;
4394  x = (ssize_t) (kernel->x*2-kernel->width+1);
4395  y = (ssize_t) (kernel->y*2-kernel->height+1);
4396  kernel->x = (ssize_t) ( -y +(ssize_t) kernel->width-1)/2;
4397  kernel->y = (ssize_t) ( +x +(ssize_t) kernel->height-1)/2;
4398  }
4399  angle = fmod(angle+270.0, 360.0); /* angle reduced 90 degrees */
4400  kernel->angle = fmod(kernel->angle+90.0, 360.0);
4401  }
4402  else
4403  perror("Unable to rotate a non-square, non-linear kernel 90 degrees");
4404  }
4405  if ( 135.0 < angle && angle <= 225.0 )
4406  {
4407  /* For a 180 degree rotation - also know as a reflection
4408  * This is actually a very very common operation!
4409  * Basically all that is needed is a reversal of the kernel data!
4410  * And a reflection of the origon
4411  */
4412  MagickRealType
4413  t;
4414 
4415  MagickRealType
4416  *k;
4417 
4418  ssize_t
4419  i,
4420  j;
4421 
4422  k=kernel->values;
4423  j=(ssize_t) (kernel->width*kernel->height-1);
4424  for (i=0; i < j; i++, j--)
4425  t=k[i], k[i]=k[j], k[j]=t;
4426 
4427  kernel->x = (ssize_t) kernel->width - kernel->x - 1;
4428  kernel->y = (ssize_t) kernel->height - kernel->y - 1;
4429  angle = fmod(angle-180.0, 360.0); /* angle+180 degrees */
4430  kernel->angle = fmod(kernel->angle+180.0, 360.0);
4431  }
4432  /* At this point angle should at least between -45 (315) and +45 degrees
4433  * In the future some form of non-orthogonal angled rotates could be
4434  * performed here, posibily with a linear kernel restriction.
4435  */
4436 
4437  return;
4438 }
4439 ␌
4440 /*
4441 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4442 % %
4443 % %
4444 % %
4445 % S c a l e G e o m e t r y K e r n e l I n f o %
4446 % %
4447 % %
4448 % %
4449 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4450 %
4451 % ScaleGeometryKernelInfo() takes a geometry argument string, typically
4452 % provided as a "-set option:convolve:scale {geometry}" user setting,
4453 % and modifies the kernel according to the parsed arguments of that setting.
4454 %
4455 % The first argument (and any normalization flags) are passed to
4456 % ScaleKernelInfo() to scale/normalize the kernel. The second argument
4457 % is then passed to UnityAddKernelInfo() to add a scled unity kernel
4458 % into the scaled/normalized kernel.
4459 %
4460 % The format of the ScaleGeometryKernelInfo method is:
4461 %
4462 % void ScaleGeometryKernelInfo(KernelInfo *kernel,
4463 % const double scaling_factor,const MagickStatusType normalize_flags)
4464 %
4465 % A description of each parameter follows:
4466 %
4467 % o kernel: the Morphology/Convolution kernel to modify
4468 %
4469 % o geometry:
4470 % The geometry string to parse, typically from the user provided
4471 % "-set option:convolve:scale {geometry}" setting.
4472 %
4473 */
4474 MagickExport void ScaleGeometryKernelInfo (KernelInfo *kernel,
4475  const char *geometry)
4476 {
4477  MagickStatusType
4478  flags;
4479 
4480  GeometryInfo
4481  args;
4482 
4483  SetGeometryInfo(&args);
4484  flags = ParseGeometry(geometry, &args);
4485 
4486 #if 0
4487  /* For Debugging Geometry Input */
4488  (void) FormatLocaleFile(stderr, "Geometry = 0x%04X : %lg x %lg %+lg %+lg\n",
4489  flags, args.rho, args.sigma, args.xi, args.psi );
4490 #endif
4491 
4492  if ( (flags & PercentValue) != 0 ) /* Handle Percentage flag*/
4493  args.rho *= 0.01, args.sigma *= 0.01;
4494 
4495  if ( (flags & RhoValue) == 0 ) /* Set Defaults for missing args */
4496  args.rho = 1.0;
4497  if ( (flags & SigmaValue) == 0 )
4498  args.sigma = 0.0;
4499 
4500  /* Scale/Normalize the input kernel */
4501  ScaleKernelInfo(kernel, args.rho, (GeometryFlags) flags);
4502 
4503  /* Add Unity Kernel, for blending with original */
4504  if ( (flags & SigmaValue) != 0 )
4505  UnityAddKernelInfo(kernel, args.sigma);
4506 
4507  return;
4508 }
4509 /*
4510 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4511 % %
4512 % %
4513 % %
4514 % S c a l e K e r n e l I n f o %
4515 % %
4516 % %
4517 % %
4518 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4519 %
4520 % ScaleKernelInfo() scales the given kernel list by the given amount, with or
4521 % without normalization of the sum of the kernel values (as per given flags).
4522 %
4523 % By default (no flags given) the values within the kernel is scaled
4524 % directly using given scaling factor without change.
4525 %
4526 % If either of the two 'normalize_flags' are given the kernel will first be
4527 % normalized and then further scaled by the scaling factor value given.
4528 %
4529 % Kernel normalization ('normalize_flags' given) is designed to ensure that
4530 % any use of the kernel scaling factor with 'Convolve' or 'Correlate'
4531 % morphology methods will fall into -1.0 to +1.0 range. Note that for
4532 % non-HDRI versions of IM this may cause images to have any negative results
4533 % clipped, unless some 'bias' is used.
4534 %
4535 % More specifically. Kernels which only contain positive values (such as a
4536 % 'Gaussian' kernel) will be scaled so that those values sum to +1.0,
4537 % ensuring a 0.0 to +1.0 output range for non-HDRI images.
4538 %
4539 % For Kernels that contain some negative values, (such as 'Sharpen' kernels)
4540 % the kernel will be scaled by the absolute of the sum of kernel values, so
4541 % that it will generally fall within the +/- 1.0 range.
4542 %
4543 % For kernels whose values sum to zero, (such as 'Laplician' kernels) kernel
4544 % will be scaled by just the sum of the postive values, so that its output
4545 % range will again fall into the +/- 1.0 range.
4546 %
4547 % For special kernels designed for locating shapes using 'Correlate', (often
4548 % only containing +1 and -1 values, representing foreground/brackground
4549 % matching) a special normalization method is provided to scale the positive
4550 % values separately to those of the negative values, so the kernel will be
4551 % forced to become a zero-sum kernel better suited to such searches.
4552 %
4553 % WARNING: Correct normalization of the kernel assumes that the '*_range'
4554 % attributes within the kernel structure have been correctly set during the
4555 % kernels creation.
4556 %
4557 % NOTE: The values used for 'normalize_flags' have been selected specifically
4558 % to match the use of geometry options, so that '!' means NormalizeValue, '^'
4559 % means CorrelateNormalizeValue. All other GeometryFlags values are ignored.
4560 %
4561 % The format of the ScaleKernelInfo method is:
4562 %
4563 % void ScaleKernelInfo(KernelInfo *kernel, const double scaling_factor,
4564 % const MagickStatusType normalize_flags )
4565 %
4566 % A description of each parameter follows:
4567 %
4568 % o kernel: the Morphology/Convolution kernel
4569 %
4570 % o scaling_factor:
4571 % multiply all values (after normalization) by this factor if not
4572 % zero. If the kernel is normalized regardless of any flags.
4573 %
4574 % o normalize_flags:
4575 % GeometryFlags defining normalization method to use.
4576 % specifically: NormalizeValue, CorrelateNormalizeValue,
4577 % and/or PercentValue
4578 %
4579 */
4580 MagickExport void ScaleKernelInfo(KernelInfo *kernel,
4581  const double scaling_factor,const GeometryFlags normalize_flags)
4582 {
4583  double
4584  pos_scale,
4585  neg_scale;
4586 
4587  ssize_t
4588  i;
4589 
4590  /* do the other kernels in a multi-kernel list first */
4591  if ( kernel->next != (KernelInfo *) NULL)
4592  ScaleKernelInfo(kernel->next, scaling_factor, normalize_flags);
4593 
4594  /* Normalization of Kernel */
4595  pos_scale = 1.0;
4596  if ( (normalize_flags&NormalizeValue) != 0 ) {
4597  if ( fabs(kernel->positive_range + kernel->negative_range) >= MagickEpsilon )
4598  /* non-zero-summing kernel (generally positive) */
4599  pos_scale = fabs(kernel->positive_range + kernel->negative_range);
4600  else
4601  /* zero-summing kernel */
4602  pos_scale = kernel->positive_range;
4603  }
4604  /* Force kernel into a normalized zero-summing kernel */
4605  if ( (normalize_flags&CorrelateNormalizeValue) != 0 ) {
4606  pos_scale = ( fabs(kernel->positive_range) >= MagickEpsilon )
4607  ? kernel->positive_range : 1.0;
4608  neg_scale = ( fabs(kernel->negative_range) >= MagickEpsilon )
4609  ? -kernel->negative_range : 1.0;
4610  }
4611  else
4612  neg_scale = pos_scale;
4613 
4614  /* finialize scaling_factor for positive and negative components */
4615  pos_scale = scaling_factor/pos_scale;
4616  neg_scale = scaling_factor/neg_scale;
4617 
4618  for (i=0; i < (ssize_t) (kernel->width*kernel->height); i++)
4619  if (!IsNaN(kernel->values[i]))
4620  kernel->values[i] *= (kernel->values[i] >= 0) ? pos_scale : neg_scale;
4621 
4622  /* convolution output range */
4623  kernel->positive_range *= pos_scale;
4624  kernel->negative_range *= neg_scale;
4625  /* maximum and minimum values in kernel */
4626  kernel->maximum *= (kernel->maximum >= 0.0) ? pos_scale : neg_scale;
4627  kernel->minimum *= (kernel->minimum >= 0.0) ? pos_scale : neg_scale;
4628 
4629  /* swap kernel settings if user's scaling factor is negative */
4630  if ( scaling_factor < MagickEpsilon ) {
4631  double t;
4632  t = kernel->positive_range;
4633  kernel->positive_range = kernel->negative_range;
4634  kernel->negative_range = t;
4635  t = kernel->maximum;
4636  kernel->maximum = kernel->minimum;
4637  kernel->minimum = 1;
4638  }
4639 
4640  return;
4641 }
4642 ␌
4643 /*
4644 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4645 % %
4646 % %
4647 % %
4648 % S h o w K e r n e l I n f o %
4649 % %
4650 % %
4651 % %
4652 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4653 %
4654 % ShowKernelInfo() outputs the details of the given kernel defination to
4655 % standard error, generally due to a users 'morphology:showKernel' option
4656 % request.
4657 %
4658 % The format of the ShowKernel method is:
4659 %
4660 % void ShowKernelInfo(const KernelInfo *kernel)
4661 %
4662 % A description of each parameter follows:
4663 %
4664 % o kernel: the Morphology/Convolution kernel
4665 %
4666 */
4667 MagickPrivate void ShowKernelInfo(const KernelInfo *kernel)
4668 {
4669  const KernelInfo
4670  *k;
4671 
4672  size_t
4673  c, i, u, v;
4674 
4675  for (c=0, k=kernel; k != (KernelInfo *) NULL; c++, k=k->next ) {
4676 
4677  (void) FormatLocaleFile(stderr, "Kernel");
4678  if ( kernel->next != (KernelInfo *) NULL )
4679  (void) FormatLocaleFile(stderr, " #%lu", (unsigned long) c );
4680  (void) FormatLocaleFile(stderr, " \"%s",
4681  CommandOptionToMnemonic(MagickKernelOptions, k->type) );
4682  if ( fabs(k->angle) >= MagickEpsilon )
4683  (void) FormatLocaleFile(stderr, "@%lg", k->angle);
4684  (void) FormatLocaleFile(stderr, "\" of size %lux%lu%+ld%+ld",(unsigned long)
4685  k->width,(unsigned long) k->height,(long) k->x,(long) k->y);
4686  (void) FormatLocaleFile(stderr,
4687  " with values from %.*lg to %.*lg\n",
4688  GetMagickPrecision(), k->minimum,
4689  GetMagickPrecision(), k->maximum);
4690  (void) FormatLocaleFile(stderr, "Forming a output range from %.*lg to %.*lg",
4691  GetMagickPrecision(), k->negative_range,
4692  GetMagickPrecision(), k->positive_range);
4693  if ( fabs(k->positive_range+k->negative_range) < MagickEpsilon )
4694  (void) FormatLocaleFile(stderr, " (Zero-Summing)\n");
4695  else if ( fabs(k->positive_range+k->negative_range-1.0) < MagickEpsilon )
4696  (void) FormatLocaleFile(stderr, " (Normalized)\n");
4697  else
4698  (void) FormatLocaleFile(stderr, " (Sum %.*lg)\n",
4699  GetMagickPrecision(), k->positive_range+k->negative_range);
4700  for (i=v=0; v < k->height; v++) {
4701  (void) FormatLocaleFile(stderr, "%2lu:", (unsigned long) v );
4702  for (u=0; u < k->width; u++, i++)
4703  if (IsNaN(k->values[i]))
4704  (void) FormatLocaleFile(stderr," %*s", GetMagickPrecision()+3, "nan");
4705  else
4706  (void) FormatLocaleFile(stderr," %*.*lg", GetMagickPrecision()+3,
4707  GetMagickPrecision(), (double) k->values[i]);
4708  (void) FormatLocaleFile(stderr,"\n");
4709  }
4710  }
4711 }
4712 ␌
4713 /*
4714 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4715 % %
4716 % %
4717 % %
4718 % U n i t y A d d K e r n a l I n f o %
4719 % %
4720 % %
4721 % %
4722 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4723 %
4724 % UnityAddKernelInfo() Adds a given amount of the 'Unity' Convolution Kernel
4725 % to the given pre-scaled and normalized Kernel. This in effect adds that
4726 % amount of the original image into the resulting convolution kernel. This
4727 % value is usually provided by the user as a percentage value in the
4728 % 'convolve:scale' setting.
4729 %
4730 % The resulting effect is to convert the defined kernels into blended
4731 % soft-blurs, unsharp kernels or into sharpening kernels.
4732 %
4733 % The format of the UnityAdditionKernelInfo method is:
4734 %
4735 % void UnityAdditionKernelInfo(KernelInfo *kernel, const double scale )
4736 %
4737 % A description of each parameter follows:
4738 %
4739 % o kernel: the Morphology/Convolution kernel
4740 %
4741 % o scale:
4742 % scaling factor for the unity kernel to be added to
4743 % the given kernel.
4744 %
4745 */
4746 MagickExport void UnityAddKernelInfo(KernelInfo *kernel,
4747  const double scale)
4748 {
4749  /* do the other kernels in a multi-kernel list first */
4750  if ( kernel->next != (KernelInfo *) NULL)
4751  UnityAddKernelInfo(kernel->next, scale);
4752 
4753  /* Add the scaled unity kernel to the existing kernel */
4754  kernel->values[kernel->x+kernel->y*kernel->width] += scale;
4755  CalcKernelMetaData(kernel); /* recalculate the meta-data */
4756 
4757  return;
4758 }
4759 ␌
4760 /*
4761 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4762 % %
4763 % %
4764 % %
4765 % Z e r o K e r n e l N a n s %
4766 % %
4767 % %
4768 % %
4769 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4770 %
4771 % ZeroKernelNans() replaces any special 'nan' value that may be present in
4772 % the kernel with a zero value. This is typically done when the kernel will
4773 % be used in special hardware (GPU) convolution processors, to simply
4774 % matters.
4775 %
4776 % The format of the ZeroKernelNans method is:
4777 %
4778 % void ZeroKernelNans (KernelInfo *kernel)
4779 %
4780 % A description of each parameter follows:
4781 %
4782 % o kernel: the Morphology/Convolution kernel
4783 %
4784 */
4785 MagickPrivate void ZeroKernelNans(KernelInfo *kernel)
4786 {
4787  size_t
4788  i;
4789 
4790  /* do the other kernels in a multi-kernel list first */
4791  if (kernel->next != (KernelInfo *) NULL)
4792  ZeroKernelNans(kernel->next);
4793 
4794  for (i=0; i < (kernel->width*kernel->height); i++)
4795  if (IsNaN(kernel->values[i]))
4796  kernel->values[i]=0.0;
4797 
4798  return;
4799 }
Definition: image.h:152