/* %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % % % % % FFFFF EEEEE AAA TTTTT U U RRRR EEEEE % % F E A A T U U R R E % % FFF EEE AAAAA T U U RRRR EEE % % F E A A T U U R R E % % F EEEEE A A T UUU R R EEEEE % % % % % % MagickCore Image Feature Methods % % % % Software Design % % Cristy % % July 1992 % % % % % % Copyright 1999-2016 ImageMagick Studio LLC, a non-profit organization % % dedicated to making software imaging solutions freely available. % % % % You may not use this file except in compliance with the License. You may % % obtain a copy of the License at % % % % http://www.imagemagick.org/script/license.php % % % % Unless required by applicable law or agreed to in writing, software % % distributed under the License is distributed on an "AS IS" BASIS, % % WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. % % See the License for the specific language governing permissions and % % limitations under the License. % % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % */ /* Include declarations. */ #include "MagickCore/studio.h" #include "MagickCore/animate.h" #include "MagickCore/artifact.h" #include "MagickCore/blob.h" #include "MagickCore/blob-private.h" #include "MagickCore/cache.h" #include "MagickCore/cache-private.h" #include "MagickCore/cache-view.h" #include "MagickCore/channel.h" #include "MagickCore/client.h" #include "MagickCore/color.h" #include "MagickCore/color-private.h" #include "MagickCore/colorspace.h" #include "MagickCore/colorspace-private.h" #include "MagickCore/composite.h" #include "MagickCore/composite-private.h" #include "MagickCore/compress.h" #include "MagickCore/constitute.h" #include "MagickCore/display.h" #include "MagickCore/draw.h" #include "MagickCore/enhance.h" #include "MagickCore/exception.h" #include "MagickCore/exception-private.h" #include "MagickCore/feature.h" #include "MagickCore/gem.h" #include "MagickCore/geometry.h" #include "MagickCore/list.h" #include "MagickCore/image-private.h" #include "MagickCore/magic.h" #include "MagickCore/magick.h" #include "MagickCore/matrix.h" #include "MagickCore/memory_.h" #include "MagickCore/module.h" #include "MagickCore/monitor.h" #include "MagickCore/monitor-private.h" #include "MagickCore/morphology-private.h" #include "MagickCore/option.h" #include "MagickCore/paint.h" #include "MagickCore/pixel-accessor.h" #include "MagickCore/profile.h" #include "MagickCore/property.h" #include "MagickCore/quantize.h" #include "MagickCore/quantum-private.h" #include "MagickCore/random_.h" #include "MagickCore/resource_.h" #include "MagickCore/segment.h" #include "MagickCore/semaphore.h" #include "MagickCore/signature-private.h" #include "MagickCore/string_.h" #include "MagickCore/thread-private.h" #include "MagickCore/timer.h" #include "MagickCore/utility.h" #include "MagickCore/version.h" /* %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % % % % % C a n n y E d g e I m a g e % % % % % % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % CannyEdgeImage() uses a multi-stage algorithm to detect a wide range of % edges in images. % % The format of the CannyEdgeImage method is: % % Image *CannyEdgeImage(const Image *image,const double radius, % const double sigma,const double lower_percent, % const double upper_percent,ExceptionInfo *exception) % % A description of each parameter follows: % % o image: the image. % % o radius: the radius of the gaussian smoothing filter. % % o sigma: the sigma of the gaussian smoothing filter. % % o lower_precent: percentage of edge pixels in the lower threshold. % % o upper_percent: percentage of edge pixels in the upper threshold. % % o exception: return any errors or warnings in this structure. % */ typedef struct _CannyInfo { double magnitude, intensity; int orientation; ssize_t x, y; } CannyInfo; static inline MagickBooleanType IsAuthenticPixel(const Image *image, const ssize_t x,const ssize_t y) { if ((x < 0) || (x >= (ssize_t) image->columns)) return(MagickFalse); if ((y < 0) || (y >= (ssize_t) image->rows)) return(MagickFalse); return(MagickTrue); } static MagickBooleanType TraceEdges(Image *edge_image,CacheView *edge_view, MatrixInfo *canny_cache,const ssize_t x,const ssize_t y, const double lower_threshold,ExceptionInfo *exception) { CannyInfo edge, pixel; MagickBooleanType status; register Quantum *q; register ssize_t i; q=GetCacheViewAuthenticPixels(edge_view,x,y,1,1,exception); if (q == (Quantum *) NULL) return(MagickFalse); *q=QuantumRange; status=SyncCacheViewAuthenticPixels(edge_view,exception); if (status == MagickFalse) return(MagickFalse);; if (GetMatrixElement(canny_cache,0,0,&edge) == MagickFalse) return(MagickFalse); edge.x=x; edge.y=y; if (SetMatrixElement(canny_cache,0,0,&edge) == MagickFalse) return(MagickFalse); for (i=1; i != 0; ) { ssize_t v; i--; status=GetMatrixElement(canny_cache,i,0,&edge); if (status == MagickFalse) return(MagickFalse); for (v=(-1); v <= 1; v++) { ssize_t u; for (u=(-1); u <= 1; u++) { if ((u == 0) && (v == 0)) continue; if (IsAuthenticPixel(edge_image,edge.x+u,edge.y+v) == MagickFalse) continue; /* Not an edge if gradient value is below the lower threshold. */ q=GetCacheViewAuthenticPixels(edge_view,edge.x+u,edge.y+v,1,1, exception); if (q == (Quantum *) NULL) return(MagickFalse); status=GetMatrixElement(canny_cache,edge.x+u,edge.y+v,&pixel); if (status == MagickFalse) return(MagickFalse); if ((GetPixelIntensity(edge_image,q) == 0.0) && (pixel.intensity >= lower_threshold)) { *q=QuantumRange; status=SyncCacheViewAuthenticPixels(edge_view,exception); if (status == MagickFalse) return(MagickFalse); edge.x+=u; edge.y+=v; status=SetMatrixElement(canny_cache,i,0,&edge); if (status == MagickFalse) return(MagickFalse); i++; } } } } return(MagickTrue); } MagickExport Image *CannyEdgeImage(const Image *image,const double radius, const double sigma,const double lower_percent,const double upper_percent, ExceptionInfo *exception) { #define CannyEdgeImageTag "CannyEdge/Image" CacheView *edge_view; CannyInfo element; char geometry[MagickPathExtent]; double lower_threshold, max, min, upper_threshold; Image *edge_image; KernelInfo *kernel_info; MagickBooleanType status; MagickOffsetType progress; MatrixInfo *canny_cache; ssize_t y; assert(image != (const Image *) NULL); assert(image->signature == MagickCoreSignature); if (image->debug != MagickFalse) (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename); assert(exception != (ExceptionInfo *) NULL); assert(exception->signature == MagickCoreSignature); /* Filter out noise. */ (void) FormatLocaleString(geometry,MagickPathExtent, "blur:%.20gx%.20g;blur:%.20gx%.20g+90",radius,sigma,radius,sigma); kernel_info=AcquireKernelInfo(geometry,exception); if (kernel_info == (KernelInfo *) NULL) ThrowImageException(ResourceLimitError,"MemoryAllocationFailed"); edge_image=ConvolveImage(image, kernel_info, exception); kernel_info=DestroyKernelInfo(kernel_info); if (edge_image == (Image *) NULL) return((Image *) NULL); if (SetImageColorspace(edge_image,GRAYColorspace,exception) == MagickFalse) { edge_image=DestroyImage(edge_image); return((Image *) NULL); } (void) SetImageAlphaChannel(edge_image,OffAlphaChannel,exception); /* Find the intensity gradient of the image. */ canny_cache=AcquireMatrixInfo(edge_image->columns,edge_image->rows, sizeof(CannyInfo),exception); if (canny_cache == (MatrixInfo *) NULL) { edge_image=DestroyImage(edge_image); return((Image *) NULL); } status=MagickTrue; edge_view=AcquireVirtualCacheView(edge_image,exception); #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp parallel for schedule(static,4) shared(status) \ magick_threads(edge_image,edge_image,edge_image->rows,1) #endif for (y=0; y < (ssize_t) edge_image->rows; y++) { register const Quantum *magick_restrict p; register ssize_t x; if (status == MagickFalse) continue; p=GetCacheViewVirtualPixels(edge_view,0,y,edge_image->columns+1,2, exception); if (p == (const Quantum *) NULL) { status=MagickFalse; continue; } for (x=0; x < (ssize_t) edge_image->columns; x++) { CannyInfo pixel; double dx, dy; register const Quantum *magick_restrict kernel_pixels; ssize_t v; static double Gx[2][2] = { { -1.0, +1.0 }, { -1.0, +1.0 } }, Gy[2][2] = { { +1.0, +1.0 }, { -1.0, -1.0 } }; (void) ResetMagickMemory(&pixel,0,sizeof(pixel)); dx=0.0; dy=0.0; kernel_pixels=p; for (v=0; v < 2; v++) { ssize_t u; for (u=0; u < 2; u++) { double intensity; intensity=GetPixelIntensity(edge_image,kernel_pixels+u); dx+=0.5*Gx[v][u]*intensity; dy+=0.5*Gy[v][u]*intensity; } kernel_pixels+=edge_image->columns+1; } pixel.magnitude=hypot(dx,dy); pixel.orientation=0; if (fabs(dx) > MagickEpsilon) { double slope; slope=dy/dx; if (slope < 0.0) { if (slope < -2.41421356237) pixel.orientation=0; else if (slope < -0.414213562373) pixel.orientation=1; else pixel.orientation=2; } else { if (slope > 2.41421356237) pixel.orientation=0; else if (slope > 0.414213562373) pixel.orientation=3; else pixel.orientation=2; } } if (SetMatrixElement(canny_cache,x,y,&pixel) == MagickFalse) continue; p+=GetPixelChannels(edge_image); } } edge_view=DestroyCacheView(edge_view); /* Non-maxima suppression, remove pixels that are not considered to be part of an edge. */ progress=0; (void) GetMatrixElement(canny_cache,0,0,&element); max=element.intensity; min=element.intensity; edge_view=AcquireAuthenticCacheView(edge_image,exception); #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp parallel for schedule(static,4) shared(status) \ magick_threads(edge_image,edge_image,edge_image->rows,1) #endif for (y=0; y < (ssize_t) edge_image->rows; y++) { register Quantum *magick_restrict q; register ssize_t x; if (status == MagickFalse) continue; q=GetCacheViewAuthenticPixels(edge_view,0,y,edge_image->columns,1, exception); if (q == (Quantum *) NULL) { status=MagickFalse; continue; } for (x=0; x < (ssize_t) edge_image->columns; x++) { CannyInfo alpha_pixel, beta_pixel, pixel; (void) GetMatrixElement(canny_cache,x,y,&pixel); switch (pixel.orientation) { case 0: default: { /* 0 degrees, north and south. */ (void) GetMatrixElement(canny_cache,x,y-1,&alpha_pixel); (void) GetMatrixElement(canny_cache,x,y+1,&beta_pixel); break; } case 1: { /* 45 degrees, northwest and southeast. */ (void) GetMatrixElement(canny_cache,x-1,y-1,&alpha_pixel); (void) GetMatrixElement(canny_cache,x+1,y+1,&beta_pixel); break; } case 2: { /* 90 degrees, east and west. */ (void) GetMatrixElement(canny_cache,x-1,y,&alpha_pixel); (void) GetMatrixElement(canny_cache,x+1,y,&beta_pixel); break; } case 3: { /* 135 degrees, northeast and southwest. */ (void) GetMatrixElement(canny_cache,x+1,y-1,&beta_pixel); (void) GetMatrixElement(canny_cache,x-1,y+1,&alpha_pixel); break; } } pixel.intensity=pixel.magnitude; if ((pixel.magnitude < alpha_pixel.magnitude) || (pixel.magnitude < beta_pixel.magnitude)) pixel.intensity=0; (void) SetMatrixElement(canny_cache,x,y,&pixel); #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp critical (MagickCore_CannyEdgeImage) #endif { if (pixel.intensity < min) min=pixel.intensity; if (pixel.intensity > max) max=pixel.intensity; } *q=0; q+=GetPixelChannels(edge_image); } if (SyncCacheViewAuthenticPixels(edge_view,exception) == MagickFalse) status=MagickFalse; } edge_view=DestroyCacheView(edge_view); /* Estimate hysteresis threshold. */ lower_threshold=lower_percent*(max-min)+min; upper_threshold=upper_percent*(max-min)+min; /* Hysteresis threshold. */ edge_view=AcquireAuthenticCacheView(edge_image,exception); for (y=0; y < (ssize_t) edge_image->rows; y++) { register ssize_t x; if (status == MagickFalse) continue; for (x=0; x < (ssize_t) edge_image->columns; x++) { CannyInfo pixel; register const Quantum *magick_restrict p; /* Edge if pixel gradient higher than upper threshold. */ p=GetCacheViewVirtualPixels(edge_view,x,y,1,1,exception); if (p == (const Quantum *) NULL) continue; status=GetMatrixElement(canny_cache,x,y,&pixel); if (status == MagickFalse) continue; if ((GetPixelIntensity(edge_image,p) == 0.0) && (pixel.intensity >= upper_threshold)) status=TraceEdges(edge_image,edge_view,canny_cache,x,y,lower_threshold, exception); } if (image->progress_monitor != (MagickProgressMonitor) NULL) { MagickBooleanType proceed; #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp critical (MagickCore_CannyEdgeImage) #endif proceed=SetImageProgress(image,CannyEdgeImageTag,progress++, image->rows); if (proceed == MagickFalse) status=MagickFalse; } } edge_view=DestroyCacheView(edge_view); /* Free resources. */ canny_cache=DestroyMatrixInfo(canny_cache); return(edge_image); } /* %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % % % % % G e t I m a g e F e a t u r e s % % % % % % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % GetImageFeatures() returns features for each channel in the image in % each of four directions (horizontal, vertical, left and right diagonals) % for the specified distance. The features include the angular second % moment, contrast, correlation, sum of squares: variance, inverse difference % moment, sum average, sum varience, sum entropy, entropy, difference variance,% difference entropy, information measures of correlation 1, information % measures of correlation 2, and maximum correlation coefficient. You can % access the red channel contrast, for example, like this: % % channel_features=GetImageFeatures(image,1,exception); % contrast=channel_features[RedPixelChannel].contrast[0]; % % Use MagickRelinquishMemory() to free the features buffer. % % The format of the GetImageFeatures method is: % % ChannelFeatures *GetImageFeatures(const Image *image, % const size_t distance,ExceptionInfo *exception) % % A description of each parameter follows: % % o image: the image. % % o distance: the distance. % % o exception: return any errors or warnings in this structure. % */ static inline double MagickLog10(const double x) { #define Log10Epsilon (1.0e-11) if (fabs(x) < Log10Epsilon) return(log10(Log10Epsilon)); return(log10(fabs(x))); } MagickExport ChannelFeatures *GetImageFeatures(const Image *image, const size_t distance,ExceptionInfo *exception) { typedef struct _ChannelStatistics { PixelInfo direction[4]; /* horizontal, vertical, left and right diagonals */ } ChannelStatistics; CacheView *image_view; ChannelFeatures *channel_features; ChannelStatistics **cooccurrence, correlation, *density_x, *density_xy, *density_y, entropy_x, entropy_xy, entropy_xy1, entropy_xy2, entropy_y, mean, **Q, *sum, sum_squares, variance; PixelPacket gray, *grays; MagickBooleanType status; register ssize_t i, r; size_t length; unsigned int number_grays; assert(image != (Image *) NULL); assert(image->signature == MagickCoreSignature); if (image->debug != MagickFalse) (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename); if ((image->columns < (distance+1)) || (image->rows < (distance+1))) return((ChannelFeatures *) NULL); length=MaxPixelChannels+1UL; channel_features=(ChannelFeatures *) AcquireQuantumMemory(length, sizeof(*channel_features)); if (channel_features == (ChannelFeatures *) NULL) ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed"); (void) ResetMagickMemory(channel_features,0,length* sizeof(*channel_features)); /* Form grays. */ grays=(PixelPacket *) AcquireQuantumMemory(MaxMap+1UL,sizeof(*grays)); if (grays == (PixelPacket *) NULL) { channel_features=(ChannelFeatures *) RelinquishMagickMemory( channel_features); (void) ThrowMagickException(exception,GetMagickModule(), ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename); return(channel_features); } for (i=0; i <= (ssize_t) MaxMap; i++) { grays[i].red=(~0U); grays[i].green=(~0U); grays[i].blue=(~0U); grays[i].alpha=(~0U); grays[i].black=(~0U); } status=MagickTrue; image_view=AcquireVirtualCacheView(image,exception); #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp parallel for schedule(static,4) shared(status) \ magick_threads(image,image,image->rows,1) #endif for (r=0; r < (ssize_t) image->rows; r++) { register const Quantum *magick_restrict p; register ssize_t x; if (status == MagickFalse) continue; p=GetCacheViewVirtualPixels(image_view,0,r,image->columns,1,exception); if (p == (const Quantum *) NULL) { status=MagickFalse; continue; } for (x=0; x < (ssize_t) image->columns; x++) { grays[ScaleQuantumToMap(GetPixelRed(image,p))].red= ScaleQuantumToMap(GetPixelRed(image,p)); grays[ScaleQuantumToMap(GetPixelGreen(image,p))].green= ScaleQuantumToMap(GetPixelGreen(image,p)); grays[ScaleQuantumToMap(GetPixelBlue(image,p))].blue= ScaleQuantumToMap(GetPixelBlue(image,p)); if (image->colorspace == CMYKColorspace) grays[ScaleQuantumToMap(GetPixelBlack(image,p))].black= ScaleQuantumToMap(GetPixelBlack(image,p)); if (image->alpha_trait != UndefinedPixelTrait) grays[ScaleQuantumToMap(GetPixelAlpha(image,p))].alpha= ScaleQuantumToMap(GetPixelAlpha(image,p)); p+=GetPixelChannels(image); } } image_view=DestroyCacheView(image_view); if (status == MagickFalse) { grays=(PixelPacket *) RelinquishMagickMemory(grays); channel_features=(ChannelFeatures *) RelinquishMagickMemory( channel_features); return(channel_features); } (void) ResetMagickMemory(&gray,0,sizeof(gray)); for (i=0; i <= (ssize_t) MaxMap; i++) { if (grays[i].red != ~0U) grays[gray.red++].red=grays[i].red; if (grays[i].green != ~0U) grays[gray.green++].green=grays[i].green; if (grays[i].blue != ~0U) grays[gray.blue++].blue=grays[i].blue; if (image->colorspace == CMYKColorspace) if (grays[i].black != ~0U) grays[gray.black++].black=grays[i].black; if (image->alpha_trait != UndefinedPixelTrait) if (grays[i].alpha != ~0U) grays[gray.alpha++].alpha=grays[i].alpha; } /* Allocate spatial dependence matrix. */ number_grays=gray.red; if (gray.green > number_grays) number_grays=gray.green; if (gray.blue > number_grays) number_grays=gray.blue; if (image->colorspace == CMYKColorspace) if (gray.black > number_grays) number_grays=gray.black; if (image->alpha_trait != UndefinedPixelTrait) if (gray.alpha > number_grays) number_grays=gray.alpha; cooccurrence=(ChannelStatistics **) AcquireQuantumMemory(number_grays, sizeof(*cooccurrence)); density_x=(ChannelStatistics *) AcquireQuantumMemory(2*(number_grays+1), sizeof(*density_x)); density_xy=(ChannelStatistics *) AcquireQuantumMemory(2*(number_grays+1), sizeof(*density_xy)); density_y=(ChannelStatistics *) AcquireQuantumMemory(2*(number_grays+1), sizeof(*density_y)); Q=(ChannelStatistics **) AcquireQuantumMemory(number_grays,sizeof(*Q)); sum=(ChannelStatistics *) AcquireQuantumMemory(number_grays,sizeof(*sum)); if ((cooccurrence == (ChannelStatistics **) NULL) || (density_x == (ChannelStatistics *) NULL) || (density_xy == (ChannelStatistics *) NULL) || (density_y == (ChannelStatistics *) NULL) || (Q == (ChannelStatistics **) NULL) || (sum == (ChannelStatistics *) NULL)) { if (Q != (ChannelStatistics **) NULL) { for (i=0; i < (ssize_t) number_grays; i++) Q[i]=(ChannelStatistics *) RelinquishMagickMemory(Q[i]); Q=(ChannelStatistics **) RelinquishMagickMemory(Q); } if (sum != (ChannelStatistics *) NULL) sum=(ChannelStatistics *) RelinquishMagickMemory(sum); if (density_y != (ChannelStatistics *) NULL) density_y=(ChannelStatistics *) RelinquishMagickMemory(density_y); if (density_xy != (ChannelStatistics *) NULL) density_xy=(ChannelStatistics *) RelinquishMagickMemory(density_xy); if (density_x != (ChannelStatistics *) NULL) density_x=(ChannelStatistics *) RelinquishMagickMemory(density_x); if (cooccurrence != (ChannelStatistics **) NULL) { for (i=0; i < (ssize_t) number_grays; i++) cooccurrence[i]=(ChannelStatistics *) RelinquishMagickMemory(cooccurrence[i]); cooccurrence=(ChannelStatistics **) RelinquishMagickMemory( cooccurrence); } grays=(PixelPacket *) RelinquishMagickMemory(grays); channel_features=(ChannelFeatures *) RelinquishMagickMemory( channel_features); (void) ThrowMagickException(exception,GetMagickModule(), ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename); return(channel_features); } (void) ResetMagickMemory(&correlation,0,sizeof(correlation)); (void) ResetMagickMemory(density_x,0,2*(number_grays+1)*sizeof(*density_x)); (void) ResetMagickMemory(density_xy,0,2*(number_grays+1)*sizeof(*density_xy)); (void) ResetMagickMemory(density_y,0,2*(number_grays+1)*sizeof(*density_y)); (void) ResetMagickMemory(&mean,0,sizeof(mean)); (void) ResetMagickMemory(sum,0,number_grays*sizeof(*sum)); (void) ResetMagickMemory(&sum_squares,0,sizeof(sum_squares)); (void) ResetMagickMemory(density_xy,0,2*number_grays*sizeof(*density_xy)); (void) ResetMagickMemory(&entropy_x,0,sizeof(entropy_x)); (void) ResetMagickMemory(&entropy_xy,0,sizeof(entropy_xy)); (void) ResetMagickMemory(&entropy_xy1,0,sizeof(entropy_xy1)); (void) ResetMagickMemory(&entropy_xy2,0,sizeof(entropy_xy2)); (void) ResetMagickMemory(&entropy_y,0,sizeof(entropy_y)); (void) ResetMagickMemory(&variance,0,sizeof(variance)); for (i=0; i < (ssize_t) number_grays; i++) { cooccurrence[i]=(ChannelStatistics *) AcquireQuantumMemory(number_grays, sizeof(**cooccurrence)); Q[i]=(ChannelStatistics *) AcquireQuantumMemory(number_grays,sizeof(**Q)); if ((cooccurrence[i] == (ChannelStatistics *) NULL) || (Q[i] == (ChannelStatistics *) NULL)) break; (void) ResetMagickMemory(cooccurrence[i],0,number_grays* sizeof(**cooccurrence)); (void) ResetMagickMemory(Q[i],0,number_grays*sizeof(**Q)); } if (i < (ssize_t) number_grays) { for (i--; i >= 0; i--) { if (Q[i] != (ChannelStatistics *) NULL) Q[i]=(ChannelStatistics *) RelinquishMagickMemory(Q[i]); if (cooccurrence[i] != (ChannelStatistics *) NULL) cooccurrence[i]=(ChannelStatistics *) RelinquishMagickMemory(cooccurrence[i]); } Q=(ChannelStatistics **) RelinquishMagickMemory(Q); cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(cooccurrence); sum=(ChannelStatistics *) RelinquishMagickMemory(sum); density_y=(ChannelStatistics *) RelinquishMagickMemory(density_y); density_xy=(ChannelStatistics *) RelinquishMagickMemory(density_xy); density_x=(ChannelStatistics *) RelinquishMagickMemory(density_x); grays=(PixelPacket *) RelinquishMagickMemory(grays); channel_features=(ChannelFeatures *) RelinquishMagickMemory( channel_features); (void) ThrowMagickException(exception,GetMagickModule(), ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename); return(channel_features); } /* Initialize spatial dependence matrix. */ status=MagickTrue; image_view=AcquireVirtualCacheView(image,exception); for (r=0; r < (ssize_t) image->rows; r++) { register const Quantum *magick_restrict p; register ssize_t x; ssize_t offset, u, v; if (status == MagickFalse) continue; p=GetCacheViewVirtualPixels(image_view,-(ssize_t) distance,r,image->columns+ 2*distance,distance+2,exception); if (p == (const Quantum *) NULL) { status=MagickFalse; continue; } p+=distance*GetPixelChannels(image);; for (x=0; x < (ssize_t) image->columns; x++) { for (i=0; i < 4; i++) { switch (i) { case 0: default: { /* Horizontal adjacency. */ offset=(ssize_t) distance; break; } case 1: { /* Vertical adjacency. */ offset=(ssize_t) (image->columns+2*distance); break; } case 2: { /* Right diagonal adjacency. */ offset=(ssize_t) ((image->columns+2*distance)-distance); break; } case 3: { /* Left diagonal adjacency. */ offset=(ssize_t) ((image->columns+2*distance)+distance); break; } } u=0; v=0; while (grays[u].red != ScaleQuantumToMap(GetPixelRed(image,p))) u++; while (grays[v].red != ScaleQuantumToMap(GetPixelRed(image,p+offset*GetPixelChannels(image)))) v++; cooccurrence[u][v].direction[i].red++; cooccurrence[v][u].direction[i].red++; u=0; v=0; while (grays[u].green != ScaleQuantumToMap(GetPixelGreen(image,p))) u++; while (grays[v].green != ScaleQuantumToMap(GetPixelGreen(image,p+offset*GetPixelChannels(image)))) v++; cooccurrence[u][v].direction[i].green++; cooccurrence[v][u].direction[i].green++; u=0; v=0; while (grays[u].blue != ScaleQuantumToMap(GetPixelBlue(image,p))) u++; while (grays[v].blue != ScaleQuantumToMap(GetPixelBlue(image,p+offset*GetPixelChannels(image)))) v++; cooccurrence[u][v].direction[i].blue++; cooccurrence[v][u].direction[i].blue++; if (image->colorspace == CMYKColorspace) { u=0; v=0; while (grays[u].black != ScaleQuantumToMap(GetPixelBlack(image,p))) u++; while (grays[v].black != ScaleQuantumToMap(GetPixelBlack(image,p+offset*GetPixelChannels(image)))) v++; cooccurrence[u][v].direction[i].black++; cooccurrence[v][u].direction[i].black++; } if (image->alpha_trait != UndefinedPixelTrait) { u=0; v=0; while (grays[u].alpha != ScaleQuantumToMap(GetPixelAlpha(image,p))) u++; while (grays[v].alpha != ScaleQuantumToMap(GetPixelAlpha(image,p+offset*GetPixelChannels(image)))) v++; cooccurrence[u][v].direction[i].alpha++; cooccurrence[v][u].direction[i].alpha++; } } p+=GetPixelChannels(image); } } grays=(PixelPacket *) RelinquishMagickMemory(grays); image_view=DestroyCacheView(image_view); if (status == MagickFalse) { for (i=0; i < (ssize_t) number_grays; i++) cooccurrence[i]=(ChannelStatistics *) RelinquishMagickMemory(cooccurrence[i]); cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(cooccurrence); channel_features=(ChannelFeatures *) RelinquishMagickMemory( channel_features); (void) ThrowMagickException(exception,GetMagickModule(), ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename); return(channel_features); } /* Normalize spatial dependence matrix. */ for (i=0; i < 4; i++) { double normalize; register ssize_t y; switch (i) { case 0: default: { /* Horizontal adjacency. */ normalize=2.0*image->rows*(image->columns-distance); break; } case 1: { /* Vertical adjacency. */ normalize=2.0*(image->rows-distance)*image->columns; break; } case 2: { /* Right diagonal adjacency. */ normalize=2.0*(image->rows-distance)*(image->columns-distance); break; } case 3: { /* Left diagonal adjacency. */ normalize=2.0*(image->rows-distance)*(image->columns-distance); break; } } normalize=PerceptibleReciprocal(normalize); for (y=0; y < (ssize_t) number_grays; y++) { register ssize_t x; for (x=0; x < (ssize_t) number_grays; x++) { cooccurrence[x][y].direction[i].red*=normalize; cooccurrence[x][y].direction[i].green*=normalize; cooccurrence[x][y].direction[i].blue*=normalize; if (image->colorspace == CMYKColorspace) cooccurrence[x][y].direction[i].black*=normalize; if (image->alpha_trait != UndefinedPixelTrait) cooccurrence[x][y].direction[i].alpha*=normalize; } } } /* Compute texture features. */ #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp parallel for schedule(static,4) shared(status) \ magick_threads(image,image,number_grays,1) #endif for (i=0; i < 4; i++) { register ssize_t y; for (y=0; y < (ssize_t) number_grays; y++) { register ssize_t x; for (x=0; x < (ssize_t) number_grays; x++) { /* Angular second moment: measure of homogeneity of the image. */ channel_features[RedPixelChannel].angular_second_moment[i]+= cooccurrence[x][y].direction[i].red* cooccurrence[x][y].direction[i].red; channel_features[GreenPixelChannel].angular_second_moment[i]+= cooccurrence[x][y].direction[i].green* cooccurrence[x][y].direction[i].green; channel_features[BluePixelChannel].angular_second_moment[i]+= cooccurrence[x][y].direction[i].blue* cooccurrence[x][y].direction[i].blue; if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].angular_second_moment[i]+= cooccurrence[x][y].direction[i].black* cooccurrence[x][y].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].angular_second_moment[i]+= cooccurrence[x][y].direction[i].alpha* cooccurrence[x][y].direction[i].alpha; /* Correlation: measure of linear-dependencies in the image. */ sum[y].direction[i].red+=cooccurrence[x][y].direction[i].red; sum[y].direction[i].green+=cooccurrence[x][y].direction[i].green; sum[y].direction[i].blue+=cooccurrence[x][y].direction[i].blue; if (image->colorspace == CMYKColorspace) sum[y].direction[i].black+=cooccurrence[x][y].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) sum[y].direction[i].alpha+=cooccurrence[x][y].direction[i].alpha; correlation.direction[i].red+=x*y*cooccurrence[x][y].direction[i].red; correlation.direction[i].green+=x*y* cooccurrence[x][y].direction[i].green; correlation.direction[i].blue+=x*y* cooccurrence[x][y].direction[i].blue; if (image->colorspace == CMYKColorspace) correlation.direction[i].black+=x*y* cooccurrence[x][y].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) correlation.direction[i].alpha+=x*y* cooccurrence[x][y].direction[i].alpha; /* Inverse Difference Moment. */ channel_features[RedPixelChannel].inverse_difference_moment[i]+= cooccurrence[x][y].direction[i].red/((y-x)*(y-x)+1); channel_features[GreenPixelChannel].inverse_difference_moment[i]+= cooccurrence[x][y].direction[i].green/((y-x)*(y-x)+1); channel_features[BluePixelChannel].inverse_difference_moment[i]+= cooccurrence[x][y].direction[i].blue/((y-x)*(y-x)+1); if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].inverse_difference_moment[i]+= cooccurrence[x][y].direction[i].black/((y-x)*(y-x)+1); if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].inverse_difference_moment[i]+= cooccurrence[x][y].direction[i].alpha/((y-x)*(y-x)+1); /* Sum average. */ density_xy[y+x+2].direction[i].red+= cooccurrence[x][y].direction[i].red; density_xy[y+x+2].direction[i].green+= cooccurrence[x][y].direction[i].green; density_xy[y+x+2].direction[i].blue+= cooccurrence[x][y].direction[i].blue; if (image->colorspace == CMYKColorspace) density_xy[y+x+2].direction[i].black+= cooccurrence[x][y].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) density_xy[y+x+2].direction[i].alpha+= cooccurrence[x][y].direction[i].alpha; /* Entropy. */ channel_features[RedPixelChannel].entropy[i]-= cooccurrence[x][y].direction[i].red* MagickLog10(cooccurrence[x][y].direction[i].red); channel_features[GreenPixelChannel].entropy[i]-= cooccurrence[x][y].direction[i].green* MagickLog10(cooccurrence[x][y].direction[i].green); channel_features[BluePixelChannel].entropy[i]-= cooccurrence[x][y].direction[i].blue* MagickLog10(cooccurrence[x][y].direction[i].blue); if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].entropy[i]-= cooccurrence[x][y].direction[i].black* MagickLog10(cooccurrence[x][y].direction[i].black); if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].entropy[i]-= cooccurrence[x][y].direction[i].alpha* MagickLog10(cooccurrence[x][y].direction[i].alpha); /* Information Measures of Correlation. */ density_x[x].direction[i].red+=cooccurrence[x][y].direction[i].red; density_x[x].direction[i].green+=cooccurrence[x][y].direction[i].green; density_x[x].direction[i].blue+=cooccurrence[x][y].direction[i].blue; if (image->alpha_trait != UndefinedPixelTrait) density_x[x].direction[i].alpha+= cooccurrence[x][y].direction[i].alpha; if (image->colorspace == CMYKColorspace) density_x[x].direction[i].black+= cooccurrence[x][y].direction[i].black; density_y[y].direction[i].red+=cooccurrence[x][y].direction[i].red; density_y[y].direction[i].green+=cooccurrence[x][y].direction[i].green; density_y[y].direction[i].blue+=cooccurrence[x][y].direction[i].blue; if (image->colorspace == CMYKColorspace) density_y[y].direction[i].black+= cooccurrence[x][y].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) density_y[y].direction[i].alpha+= cooccurrence[x][y].direction[i].alpha; } mean.direction[i].red+=y*sum[y].direction[i].red; sum_squares.direction[i].red+=y*y*sum[y].direction[i].red; mean.direction[i].green+=y*sum[y].direction[i].green; sum_squares.direction[i].green+=y*y*sum[y].direction[i].green; mean.direction[i].blue+=y*sum[y].direction[i].blue; sum_squares.direction[i].blue+=y*y*sum[y].direction[i].blue; if (image->colorspace == CMYKColorspace) { mean.direction[i].black+=y*sum[y].direction[i].black; sum_squares.direction[i].black+=y*y*sum[y].direction[i].black; } if (image->alpha_trait != UndefinedPixelTrait) { mean.direction[i].alpha+=y*sum[y].direction[i].alpha; sum_squares.direction[i].alpha+=y*y*sum[y].direction[i].alpha; } } /* Correlation: measure of linear-dependencies in the image. */ channel_features[RedPixelChannel].correlation[i]= (correlation.direction[i].red-mean.direction[i].red* mean.direction[i].red)/(sqrt(sum_squares.direction[i].red- (mean.direction[i].red*mean.direction[i].red))*sqrt( sum_squares.direction[i].red-(mean.direction[i].red* mean.direction[i].red))); channel_features[GreenPixelChannel].correlation[i]= (correlation.direction[i].green-mean.direction[i].green* mean.direction[i].green)/(sqrt(sum_squares.direction[i].green- (mean.direction[i].green*mean.direction[i].green))*sqrt( sum_squares.direction[i].green-(mean.direction[i].green* mean.direction[i].green))); channel_features[BluePixelChannel].correlation[i]= (correlation.direction[i].blue-mean.direction[i].blue* mean.direction[i].blue)/(sqrt(sum_squares.direction[i].blue- (mean.direction[i].blue*mean.direction[i].blue))*sqrt( sum_squares.direction[i].blue-(mean.direction[i].blue* mean.direction[i].blue))); if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].correlation[i]= (correlation.direction[i].black-mean.direction[i].black* mean.direction[i].black)/(sqrt(sum_squares.direction[i].black- (mean.direction[i].black*mean.direction[i].black))*sqrt( sum_squares.direction[i].black-(mean.direction[i].black* mean.direction[i].black))); if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].correlation[i]= (correlation.direction[i].alpha-mean.direction[i].alpha* mean.direction[i].alpha)/(sqrt(sum_squares.direction[i].alpha- (mean.direction[i].alpha*mean.direction[i].alpha))*sqrt( sum_squares.direction[i].alpha-(mean.direction[i].alpha* mean.direction[i].alpha))); } /* Compute more texture features. */ #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp parallel for schedule(static,4) shared(status) \ magick_threads(image,image,number_grays,1) #endif for (i=0; i < 4; i++) { register ssize_t x; for (x=2; x < (ssize_t) (2*number_grays); x++) { /* Sum average. */ channel_features[RedPixelChannel].sum_average[i]+= x*density_xy[x].direction[i].red; channel_features[GreenPixelChannel].sum_average[i]+= x*density_xy[x].direction[i].green; channel_features[BluePixelChannel].sum_average[i]+= x*density_xy[x].direction[i].blue; if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].sum_average[i]+= x*density_xy[x].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].sum_average[i]+= x*density_xy[x].direction[i].alpha; /* Sum entropy. */ channel_features[RedPixelChannel].sum_entropy[i]-= density_xy[x].direction[i].red* MagickLog10(density_xy[x].direction[i].red); channel_features[GreenPixelChannel].sum_entropy[i]-= density_xy[x].direction[i].green* MagickLog10(density_xy[x].direction[i].green); channel_features[BluePixelChannel].sum_entropy[i]-= density_xy[x].direction[i].blue* MagickLog10(density_xy[x].direction[i].blue); if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].sum_entropy[i]-= density_xy[x].direction[i].black* MagickLog10(density_xy[x].direction[i].black); if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].sum_entropy[i]-= density_xy[x].direction[i].alpha* MagickLog10(density_xy[x].direction[i].alpha); /* Sum variance. */ channel_features[RedPixelChannel].sum_variance[i]+= (x-channel_features[RedPixelChannel].sum_entropy[i])* (x-channel_features[RedPixelChannel].sum_entropy[i])* density_xy[x].direction[i].red; channel_features[GreenPixelChannel].sum_variance[i]+= (x-channel_features[GreenPixelChannel].sum_entropy[i])* (x-channel_features[GreenPixelChannel].sum_entropy[i])* density_xy[x].direction[i].green; channel_features[BluePixelChannel].sum_variance[i]+= (x-channel_features[BluePixelChannel].sum_entropy[i])* (x-channel_features[BluePixelChannel].sum_entropy[i])* density_xy[x].direction[i].blue; if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].sum_variance[i]+= (x-channel_features[BlackPixelChannel].sum_entropy[i])* (x-channel_features[BlackPixelChannel].sum_entropy[i])* density_xy[x].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].sum_variance[i]+= (x-channel_features[AlphaPixelChannel].sum_entropy[i])* (x-channel_features[AlphaPixelChannel].sum_entropy[i])* density_xy[x].direction[i].alpha; } } /* Compute more texture features. */ #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp parallel for schedule(static,4) shared(status) \ magick_threads(image,image,number_grays,1) #endif for (i=0; i < 4; i++) { register ssize_t y; for (y=0; y < (ssize_t) number_grays; y++) { register ssize_t x; for (x=0; x < (ssize_t) number_grays; x++) { /* Sum of Squares: Variance */ variance.direction[i].red+=(y-mean.direction[i].red+1)* (y-mean.direction[i].red+1)*cooccurrence[x][y].direction[i].red; variance.direction[i].green+=(y-mean.direction[i].green+1)* (y-mean.direction[i].green+1)*cooccurrence[x][y].direction[i].green; variance.direction[i].blue+=(y-mean.direction[i].blue+1)* (y-mean.direction[i].blue+1)*cooccurrence[x][y].direction[i].blue; if (image->colorspace == CMYKColorspace) variance.direction[i].black+=(y-mean.direction[i].black+1)* (y-mean.direction[i].black+1)*cooccurrence[x][y].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) variance.direction[i].alpha+=(y-mean.direction[i].alpha+1)* (y-mean.direction[i].alpha+1)* cooccurrence[x][y].direction[i].alpha; /* Sum average / Difference Variance. */ density_xy[MagickAbsoluteValue(y-x)].direction[i].red+= cooccurrence[x][y].direction[i].red; density_xy[MagickAbsoluteValue(y-x)].direction[i].green+= cooccurrence[x][y].direction[i].green; density_xy[MagickAbsoluteValue(y-x)].direction[i].blue+= cooccurrence[x][y].direction[i].blue; if (image->colorspace == CMYKColorspace) density_xy[MagickAbsoluteValue(y-x)].direction[i].black+= cooccurrence[x][y].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) density_xy[MagickAbsoluteValue(y-x)].direction[i].alpha+= cooccurrence[x][y].direction[i].alpha; /* Information Measures of Correlation. */ entropy_xy.direction[i].red-=cooccurrence[x][y].direction[i].red* MagickLog10(cooccurrence[x][y].direction[i].red); entropy_xy.direction[i].green-=cooccurrence[x][y].direction[i].green* MagickLog10(cooccurrence[x][y].direction[i].green); entropy_xy.direction[i].blue-=cooccurrence[x][y].direction[i].blue* MagickLog10(cooccurrence[x][y].direction[i].blue); if (image->colorspace == CMYKColorspace) entropy_xy.direction[i].black-=cooccurrence[x][y].direction[i].black* MagickLog10(cooccurrence[x][y].direction[i].black); if (image->alpha_trait != UndefinedPixelTrait) entropy_xy.direction[i].alpha-= cooccurrence[x][y].direction[i].alpha*MagickLog10( cooccurrence[x][y].direction[i].alpha); entropy_xy1.direction[i].red-=(cooccurrence[x][y].direction[i].red* MagickLog10(density_x[x].direction[i].red*density_y[y].direction[i].red)); entropy_xy1.direction[i].green-=(cooccurrence[x][y].direction[i].green* MagickLog10(density_x[x].direction[i].green* density_y[y].direction[i].green)); entropy_xy1.direction[i].blue-=(cooccurrence[x][y].direction[i].blue* MagickLog10(density_x[x].direction[i].blue*density_y[y].direction[i].blue)); if (image->colorspace == CMYKColorspace) entropy_xy1.direction[i].black-=( cooccurrence[x][y].direction[i].black*MagickLog10( density_x[x].direction[i].black*density_y[y].direction[i].black)); if (image->alpha_trait != UndefinedPixelTrait) entropy_xy1.direction[i].alpha-=( cooccurrence[x][y].direction[i].alpha*MagickLog10( density_x[x].direction[i].alpha*density_y[y].direction[i].alpha)); entropy_xy2.direction[i].red-=(density_x[x].direction[i].red* density_y[y].direction[i].red*MagickLog10(density_x[x].direction[i].red* density_y[y].direction[i].red)); entropy_xy2.direction[i].green-=(density_x[x].direction[i].green* density_y[y].direction[i].green*MagickLog10(density_x[x].direction[i].green* density_y[y].direction[i].green)); entropy_xy2.direction[i].blue-=(density_x[x].direction[i].blue* density_y[y].direction[i].blue*MagickLog10(density_x[x].direction[i].blue* density_y[y].direction[i].blue)); if (image->colorspace == CMYKColorspace) entropy_xy2.direction[i].black-=(density_x[x].direction[i].black* density_y[y].direction[i].black*MagickLog10( density_x[x].direction[i].black*density_y[y].direction[i].black)); if (image->alpha_trait != UndefinedPixelTrait) entropy_xy2.direction[i].alpha-=(density_x[x].direction[i].alpha* density_y[y].direction[i].alpha*MagickLog10( density_x[x].direction[i].alpha*density_y[y].direction[i].alpha)); } } channel_features[RedPixelChannel].variance_sum_of_squares[i]= variance.direction[i].red; channel_features[GreenPixelChannel].variance_sum_of_squares[i]= variance.direction[i].green; channel_features[BluePixelChannel].variance_sum_of_squares[i]= variance.direction[i].blue; if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].variance_sum_of_squares[i]= variance.direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].variance_sum_of_squares[i]= variance.direction[i].alpha; } /* Compute more texture features. */ (void) ResetMagickMemory(&variance,0,sizeof(variance)); (void) ResetMagickMemory(&sum_squares,0,sizeof(sum_squares)); #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp parallel for schedule(static,4) shared(status) \ magick_threads(image,image,number_grays,1) #endif for (i=0; i < 4; i++) { register ssize_t x; for (x=0; x < (ssize_t) number_grays; x++) { /* Difference variance. */ variance.direction[i].red+=density_xy[x].direction[i].red; variance.direction[i].green+=density_xy[x].direction[i].green; variance.direction[i].blue+=density_xy[x].direction[i].blue; if (image->colorspace == CMYKColorspace) variance.direction[i].black+=density_xy[x].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) variance.direction[i].alpha+=density_xy[x].direction[i].alpha; sum_squares.direction[i].red+=density_xy[x].direction[i].red* density_xy[x].direction[i].red; sum_squares.direction[i].green+=density_xy[x].direction[i].green* density_xy[x].direction[i].green; sum_squares.direction[i].blue+=density_xy[x].direction[i].blue* density_xy[x].direction[i].blue; if (image->colorspace == CMYKColorspace) sum_squares.direction[i].black+=density_xy[x].direction[i].black* density_xy[x].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) sum_squares.direction[i].alpha+=density_xy[x].direction[i].alpha* density_xy[x].direction[i].alpha; /* Difference entropy. */ channel_features[RedPixelChannel].difference_entropy[i]-= density_xy[x].direction[i].red* MagickLog10(density_xy[x].direction[i].red); channel_features[GreenPixelChannel].difference_entropy[i]-= density_xy[x].direction[i].green* MagickLog10(density_xy[x].direction[i].green); channel_features[BluePixelChannel].difference_entropy[i]-= density_xy[x].direction[i].blue* MagickLog10(density_xy[x].direction[i].blue); if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].difference_entropy[i]-= density_xy[x].direction[i].black* MagickLog10(density_xy[x].direction[i].black); if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].difference_entropy[i]-= density_xy[x].direction[i].alpha* MagickLog10(density_xy[x].direction[i].alpha); /* Information Measures of Correlation. */ entropy_x.direction[i].red-=(density_x[x].direction[i].red* MagickLog10(density_x[x].direction[i].red)); entropy_x.direction[i].green-=(density_x[x].direction[i].green* MagickLog10(density_x[x].direction[i].green)); entropy_x.direction[i].blue-=(density_x[x].direction[i].blue* MagickLog10(density_x[x].direction[i].blue)); if (image->colorspace == CMYKColorspace) entropy_x.direction[i].black-=(density_x[x].direction[i].black* MagickLog10(density_x[x].direction[i].black)); if (image->alpha_trait != UndefinedPixelTrait) entropy_x.direction[i].alpha-=(density_x[x].direction[i].alpha* MagickLog10(density_x[x].direction[i].alpha)); entropy_y.direction[i].red-=(density_y[x].direction[i].red* MagickLog10(density_y[x].direction[i].red)); entropy_y.direction[i].green-=(density_y[x].direction[i].green* MagickLog10(density_y[x].direction[i].green)); entropy_y.direction[i].blue-=(density_y[x].direction[i].blue* MagickLog10(density_y[x].direction[i].blue)); if (image->colorspace == CMYKColorspace) entropy_y.direction[i].black-=(density_y[x].direction[i].black* MagickLog10(density_y[x].direction[i].black)); if (image->alpha_trait != UndefinedPixelTrait) entropy_y.direction[i].alpha-=(density_y[x].direction[i].alpha* MagickLog10(density_y[x].direction[i].alpha)); } /* Difference variance. */ channel_features[RedPixelChannel].difference_variance[i]= (((double) number_grays*number_grays*sum_squares.direction[i].red)- (variance.direction[i].red*variance.direction[i].red))/ ((double) number_grays*number_grays*number_grays*number_grays); channel_features[GreenPixelChannel].difference_variance[i]= (((double) number_grays*number_grays*sum_squares.direction[i].green)- (variance.direction[i].green*variance.direction[i].green))/ ((double) number_grays*number_grays*number_grays*number_grays); channel_features[BluePixelChannel].difference_variance[i]= (((double) number_grays*number_grays*sum_squares.direction[i].blue)- (variance.direction[i].blue*variance.direction[i].blue))/ ((double) number_grays*number_grays*number_grays*number_grays); if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].difference_variance[i]= (((double) number_grays*number_grays*sum_squares.direction[i].black)- (variance.direction[i].black*variance.direction[i].black))/ ((double) number_grays*number_grays*number_grays*number_grays); if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].difference_variance[i]= (((double) number_grays*number_grays*sum_squares.direction[i].alpha)- (variance.direction[i].alpha*variance.direction[i].alpha))/ ((double) number_grays*number_grays*number_grays*number_grays); /* Information Measures of Correlation. */ channel_features[RedPixelChannel].measure_of_correlation_1[i]= (entropy_xy.direction[i].red-entropy_xy1.direction[i].red)/ (entropy_x.direction[i].red > entropy_y.direction[i].red ? entropy_x.direction[i].red : entropy_y.direction[i].red); channel_features[GreenPixelChannel].measure_of_correlation_1[i]= (entropy_xy.direction[i].green-entropy_xy1.direction[i].green)/ (entropy_x.direction[i].green > entropy_y.direction[i].green ? entropy_x.direction[i].green : entropy_y.direction[i].green); channel_features[BluePixelChannel].measure_of_correlation_1[i]= (entropy_xy.direction[i].blue-entropy_xy1.direction[i].blue)/ (entropy_x.direction[i].blue > entropy_y.direction[i].blue ? entropy_x.direction[i].blue : entropy_y.direction[i].blue); if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].measure_of_correlation_1[i]= (entropy_xy.direction[i].black-entropy_xy1.direction[i].black)/ (entropy_x.direction[i].black > entropy_y.direction[i].black ? entropy_x.direction[i].black : entropy_y.direction[i].black); if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].measure_of_correlation_1[i]= (entropy_xy.direction[i].alpha-entropy_xy1.direction[i].alpha)/ (entropy_x.direction[i].alpha > entropy_y.direction[i].alpha ? entropy_x.direction[i].alpha : entropy_y.direction[i].alpha); channel_features[RedPixelChannel].measure_of_correlation_2[i]= (sqrt(fabs(1.0-exp(-2.0*(double) (entropy_xy2.direction[i].red- entropy_xy.direction[i].red))))); channel_features[GreenPixelChannel].measure_of_correlation_2[i]= (sqrt(fabs(1.0-exp(-2.0*(double) (entropy_xy2.direction[i].green- entropy_xy.direction[i].green))))); channel_features[BluePixelChannel].measure_of_correlation_2[i]= (sqrt(fabs(1.0-exp(-2.0*(double) (entropy_xy2.direction[i].blue- entropy_xy.direction[i].blue))))); if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].measure_of_correlation_2[i]= (sqrt(fabs(1.0-exp(-2.0*(double) (entropy_xy2.direction[i].black- entropy_xy.direction[i].black))))); if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].measure_of_correlation_2[i]= (sqrt(fabs(1.0-exp(-2.0*(double) (entropy_xy2.direction[i].alpha- entropy_xy.direction[i].alpha))))); } /* Compute more texture features. */ #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp parallel for schedule(static,4) shared(status) \ magick_threads(image,image,number_grays,1) #endif for (i=0; i < 4; i++) { ssize_t z; for (z=0; z < (ssize_t) number_grays; z++) { register ssize_t y; ChannelStatistics pixel; (void) ResetMagickMemory(&pixel,0,sizeof(pixel)); for (y=0; y < (ssize_t) number_grays; y++) { register ssize_t x; for (x=0; x < (ssize_t) number_grays; x++) { /* Contrast: amount of local variations present in an image. */ if (((y-x) == z) || ((x-y) == z)) { pixel.direction[i].red+=cooccurrence[x][y].direction[i].red; pixel.direction[i].green+=cooccurrence[x][y].direction[i].green; pixel.direction[i].blue+=cooccurrence[x][y].direction[i].blue; if (image->colorspace == CMYKColorspace) pixel.direction[i].black+=cooccurrence[x][y].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) pixel.direction[i].alpha+= cooccurrence[x][y].direction[i].alpha; } /* Maximum Correlation Coefficient. */ Q[z][y].direction[i].red+=cooccurrence[z][x].direction[i].red* cooccurrence[y][x].direction[i].red/density_x[z].direction[i].red/ density_y[x].direction[i].red; Q[z][y].direction[i].green+=cooccurrence[z][x].direction[i].green* cooccurrence[y][x].direction[i].green/ density_x[z].direction[i].green/density_y[x].direction[i].red; Q[z][y].direction[i].blue+=cooccurrence[z][x].direction[i].blue* cooccurrence[y][x].direction[i].blue/density_x[z].direction[i].blue/ density_y[x].direction[i].blue; if (image->colorspace == CMYKColorspace) Q[z][y].direction[i].black+=cooccurrence[z][x].direction[i].black* cooccurrence[y][x].direction[i].black/ density_x[z].direction[i].black/density_y[x].direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) Q[z][y].direction[i].alpha+= cooccurrence[z][x].direction[i].alpha* cooccurrence[y][x].direction[i].alpha/ density_x[z].direction[i].alpha/ density_y[x].direction[i].alpha; } } channel_features[RedPixelChannel].contrast[i]+=z*z* pixel.direction[i].red; channel_features[GreenPixelChannel].contrast[i]+=z*z* pixel.direction[i].green; channel_features[BluePixelChannel].contrast[i]+=z*z* pixel.direction[i].blue; if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].contrast[i]+=z*z* pixel.direction[i].black; if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].contrast[i]+=z*z* pixel.direction[i].alpha; } /* Maximum Correlation Coefficient. Future: return second largest eigenvalue of Q. */ channel_features[RedPixelChannel].maximum_correlation_coefficient[i]= sqrt((double) -1.0); channel_features[GreenPixelChannel].maximum_correlation_coefficient[i]= sqrt((double) -1.0); channel_features[BluePixelChannel].maximum_correlation_coefficient[i]= sqrt((double) -1.0); if (image->colorspace == CMYKColorspace) channel_features[BlackPixelChannel].maximum_correlation_coefficient[i]= sqrt((double) -1.0); if (image->alpha_trait != UndefinedPixelTrait) channel_features[AlphaPixelChannel].maximum_correlation_coefficient[i]= sqrt((double) -1.0); } /* Relinquish resources. */ sum=(ChannelStatistics *) RelinquishMagickMemory(sum); for (i=0; i < (ssize_t) number_grays; i++) Q[i]=(ChannelStatistics *) RelinquishMagickMemory(Q[i]); Q=(ChannelStatistics **) RelinquishMagickMemory(Q); density_y=(ChannelStatistics *) RelinquishMagickMemory(density_y); density_xy=(ChannelStatistics *) RelinquishMagickMemory(density_xy); density_x=(ChannelStatistics *) RelinquishMagickMemory(density_x); for (i=0; i < (ssize_t) number_grays; i++) cooccurrence[i]=(ChannelStatistics *) RelinquishMagickMemory(cooccurrence[i]); cooccurrence=(ChannelStatistics **) RelinquishMagickMemory(cooccurrence); return(channel_features); } /* %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % % % % % H o u g h L i n e I m a g e % % % % % % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % Use HoughLineImage() in conjunction with any binary edge extracted image (we % recommand Canny) to identify lines in the image. The algorithm accumulates % counts for every white pixel for every possible orientation (for angles from % 0 to 179 in 1 degree increments) and distance from the center of the image to % the corner (in 1 px increments) and stores the counts in an accumulator matrix % of angle vs distance. The size of the accumulator is 180x(diagonal/2). Next % it searches this space for peaks in counts and converts the locations of the % peaks to slope and intercept in the normal x,y input image space. Use the % slope/intercepts to find the endpoints clipped to the bounds of the image. The % lines are then drawn. The counts are a measure of the length of the lines % % The format of the HoughLineImage method is: % % Image *HoughLineImage(const Image *image,const size_t width, % const size_t height,const size_t threshold,ExceptionInfo *exception) % % A description of each parameter follows: % % o image: the image. % % o width, height: find line pairs as local maxima in this neighborhood. % % o threshold: the line count threshold. % % o exception: return any errors or warnings in this structure. % */ static inline double MagickRound(double x) { /* Round the fraction to nearest integer. */ if ((x-floor(x)) < (ceil(x)-x)) return(floor(x)); return(ceil(x)); } static Image *RenderHoughLines(const ImageInfo *image_info,const size_t columns, const size_t rows,ExceptionInfo *exception) { #define BoundingBox "viewbox" DrawInfo *draw_info; Image *image; MagickBooleanType status; /* Open image. */ image=AcquireImage(image_info,exception); status=OpenBlob(image_info,image,ReadBinaryBlobMode,exception); if (status == MagickFalse) { image=DestroyImageList(image); return((Image *) NULL); } image->columns=columns; image->rows=rows; draw_info=CloneDrawInfo(image_info,(DrawInfo *) NULL); draw_info->affine.sx=image->resolution.x == 0.0 ? 1.0 : image->resolution.x/ DefaultResolution; draw_info->affine.sy=image->resolution.y == 0.0 ? 1.0 : image->resolution.y/ DefaultResolution; image->columns=(size_t) (draw_info->affine.sx*image->columns); image->rows=(size_t) (draw_info->affine.sy*image->rows); status=SetImageExtent(image,image->columns,image->rows,exception); if (status == MagickFalse) return(DestroyImageList(image)); if (SetImageBackgroundColor(image,exception) == MagickFalse) { image=DestroyImageList(image); return((Image *) NULL); } /* Render drawing. */ if (GetBlobStreamData(image) == (unsigned char *) NULL) draw_info->primitive=FileToString(image->filename,~0UL,exception); else { draw_info->primitive=(char *) AcquireMagickMemory((size_t) GetBlobSize(image)+1); if (draw_info->primitive != (char *) NULL) { (void) CopyMagickMemory(draw_info->primitive,GetBlobStreamData(image), (size_t) GetBlobSize(image)); draw_info->primitive[GetBlobSize(image)]='\0'; } } (void) DrawImage(image,draw_info,exception); draw_info=DestroyDrawInfo(draw_info); (void) CloseBlob(image); return(GetFirstImageInList(image)); } MagickExport Image *HoughLineImage(const Image *image,const size_t width, const size_t height,const size_t threshold,ExceptionInfo *exception) { #define HoughLineImageTag "HoughLine/Image" CacheView *image_view; char message[MagickPathExtent], path[MagickPathExtent]; const char *artifact; double hough_height; Image *lines_image = NULL; ImageInfo *image_info; int file; MagickBooleanType status; MagickOffsetType progress; MatrixInfo *accumulator; PointInfo center; register ssize_t y; size_t accumulator_height, accumulator_width, line_count; /* Create the accumulator. */ assert(image != (const Image *) NULL); assert(image->signature == MagickCoreSignature); if (image->debug != MagickFalse) (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename); assert(exception != (ExceptionInfo *) NULL); assert(exception->signature == MagickCoreSignature); accumulator_width=180; hough_height=((sqrt(2.0)*(double) (image->rows > image->columns ? image->rows : image->columns))/2.0); accumulator_height=(size_t) (2.0*hough_height); accumulator=AcquireMatrixInfo(accumulator_width,accumulator_height, sizeof(double),exception); if (accumulator == (MatrixInfo *) NULL) ThrowImageException(ResourceLimitError,"MemoryAllocationFailed"); if (NullMatrix(accumulator) == MagickFalse) { accumulator=DestroyMatrixInfo(accumulator); ThrowImageException(ResourceLimitError,"MemoryAllocationFailed"); } /* Populate the accumulator. */ status=MagickTrue; progress=0; center.x=(double) image->columns/2.0; center.y=(double) image->rows/2.0; image_view=AcquireVirtualCacheView(image,exception); for (y=0; y < (ssize_t) image->rows; y++) { register const Quantum *magick_restrict p; register ssize_t x; if (status == MagickFalse) continue; p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception); if (p == (Quantum *) NULL) { status=MagickFalse; continue; } for (x=0; x < (ssize_t) image->columns; x++) { if (GetPixelIntensity(image,p) > (QuantumRange/2.0)) { register ssize_t i; for (i=0; i < 180; i++) { double count, radius; radius=(((double) x-center.x)*cos(DegreesToRadians((double) i)))+ (((double) y-center.y)*sin(DegreesToRadians((double) i))); (void) GetMatrixElement(accumulator,i,(ssize_t) MagickRound(radius+hough_height),&count); count++; (void) SetMatrixElement(accumulator,i,(ssize_t) MagickRound(radius+hough_height),&count); } } p+=GetPixelChannels(image); } if (image->progress_monitor != (MagickProgressMonitor) NULL) { MagickBooleanType proceed; #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp critical (MagickCore_CannyEdgeImage) #endif proceed=SetImageProgress(image,CannyEdgeImageTag,progress++, image->rows); if (proceed == MagickFalse) status=MagickFalse; } } image_view=DestroyCacheView(image_view); if (status == MagickFalse) { accumulator=DestroyMatrixInfo(accumulator); return((Image *) NULL); } /* Generate line segments from accumulator. */ file=AcquireUniqueFileResource(path); if (file == -1) { accumulator=DestroyMatrixInfo(accumulator); return((Image *) NULL); } (void) FormatLocaleString(message,MagickPathExtent, "# Hough line transform: %.20gx%.20g%+.20g\n",(double) width, (double) height,(double) threshold); if (write(file,message,strlen(message)) != (ssize_t) strlen(message)) status=MagickFalse; (void) FormatLocaleString(message,MagickPathExtent, "viewbox 0 0 %.20g %.20g\n",(double) image->columns,(double) image->rows); if (write(file,message,strlen(message)) != (ssize_t) strlen(message)) status=MagickFalse; line_count=image->columns > image->rows ? image->columns/4 : image->rows/4; if (threshold != 0) line_count=threshold; for (y=0; y < (ssize_t) accumulator_height; y++) { register ssize_t x; for (x=0; x < (ssize_t) accumulator_width; x++) { double count; (void) GetMatrixElement(accumulator,x,y,&count); if (count >= (double) line_count) { double maxima; SegmentInfo line; ssize_t v; /* Is point a local maxima? */ maxima=count; for (v=(-((ssize_t) height/2)); v <= (((ssize_t) height/2)); v++) { ssize_t u; for (u=(-((ssize_t) width/2)); u <= (((ssize_t) width/2)); u++) { if ((u != 0) || (v !=0)) { (void) GetMatrixElement(accumulator,x+u,y+v,&count); if (count > maxima) { maxima=count; break; } } } if (u < (ssize_t) (width/2)) break; } (void) GetMatrixElement(accumulator,x,y,&count); if (maxima > count) continue; if ((x >= 45) && (x <= 135)) { /* y = (r-x cos(t))/sin(t) */ line.x1=0.0; line.y1=((double) (y-(accumulator_height/2.0))-((line.x1- (image->columns/2.0))*cos(DegreesToRadians((double) x))))/ sin(DegreesToRadians((double) x))+(image->rows/2.0); line.x2=(double) image->columns; line.y2=((double) (y-(accumulator_height/2.0))-((line.x2- (image->columns/2.0))*cos(DegreesToRadians((double) x))))/ sin(DegreesToRadians((double) x))+(image->rows/2.0); } else { /* x = (r-y cos(t))/sin(t) */ line.y1=0.0; line.x1=((double) (y-(accumulator_height/2.0))-((line.y1- (image->rows/2.0))*sin(DegreesToRadians((double) x))))/ cos(DegreesToRadians((double) x))+(image->columns/2.0); line.y2=(double) image->rows; line.x2=((double) (y-(accumulator_height/2.0))-((line.y2- (image->rows/2.0))*sin(DegreesToRadians((double) x))))/ cos(DegreesToRadians((double) x))+(image->columns/2.0); } (void) FormatLocaleString(message,MagickPathExtent, "line %g,%g %g,%g # %g\n",line.x1,line.y1,line.x2,line.y2,maxima); if (write(file,message,strlen(message)) != (ssize_t) strlen(message)) status=MagickFalse; } } } (void) close(file); /* Render lines to image canvas. */ image_info=AcquireImageInfo(); image_info->background_color=image->background_color; (void) FormatLocaleString(image_info->filename,MagickPathExtent,"%s",path); artifact=GetImageArtifact(image,"background"); if (artifact != (const char *) NULL) (void) SetImageOption(image_info,"background",artifact); artifact=GetImageArtifact(image,"fill"); if (artifact != (const char *) NULL) (void) SetImageOption(image_info,"fill",artifact); artifact=GetImageArtifact(image,"stroke"); if (artifact != (const char *) NULL) (void) SetImageOption(image_info,"stroke",artifact); artifact=GetImageArtifact(image,"strokewidth"); if (artifact != (const char *) NULL) (void) SetImageOption(image_info,"strokewidth",artifact); lines_image=RenderHoughLines(image_info,image->columns,image->rows,exception); artifact=GetImageArtifact(image,"hough-lines:accumulator"); if ((lines_image != (Image *) NULL) && (IsStringTrue(artifact) != MagickFalse)) { Image *accumulator_image; accumulator_image=MatrixToImage(accumulator,exception); if (accumulator_image != (Image *) NULL) AppendImageToList(&lines_image,accumulator_image); } /* Free resources. */ accumulator=DestroyMatrixInfo(accumulator); image_info=DestroyImageInfo(image_info); (void) RelinquishUniqueFileResource(path); return(GetFirstImageInList(lines_image)); } /* %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % % % % % M e a n S h i f t I m a g e % % % % % % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % MeanShiftImage() delineate arbitrarily shaped clusters in the image. For % each pixel, it visits all the pixels in the neighborhood specified by % the window centered at the pixel and excludes those that are outside the % radius=(window-1)/2 surrounding the pixel. From those pixels, it finds those % that are within the specified color distance from the current mean, and % computes a new x,y centroid from those coordinates and a new mean. This new % x,y centroid is used as the center for a new window. This process iterates % until it converges and the final mean is replaces the (original window % center) pixel value. It repeats this process for the next pixel, etc., % until it processes all pixels in the image. Results are typically better with % colorspaces other than sRGB. We recommend YIQ, YUV or YCbCr. % % The format of the MeanShiftImage method is: % % Image *MeanShiftImage(const Image *image,const size_t width, % const size_t height,const double color_distance, % ExceptionInfo *exception) % % A description of each parameter follows: % % o image: the image. % % o width, height: find pixels in this neighborhood. % % o color_distance: the color distance. % % o exception: return any errors or warnings in this structure. % */ MagickExport Image *MeanShiftImage(const Image *image,const size_t width, const size_t height,const double color_distance,ExceptionInfo *exception) { #define MaxMeanShiftIterations 100 #define MeanShiftImageTag "MeanShift/Image" CacheView *image_view, *mean_view, *pixel_view; Image *mean_image; MagickBooleanType status; MagickOffsetType progress; ssize_t y; assert(image != (const Image *) NULL); assert(image->signature == MagickCoreSignature); if (image->debug != MagickFalse) (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename); assert(exception != (ExceptionInfo *) NULL); assert(exception->signature == MagickCoreSignature); mean_image=CloneImage(image,image->columns,image->rows,MagickTrue,exception); if (mean_image == (Image *) NULL) return((Image *) NULL); if (SetImageStorageClass(mean_image,DirectClass,exception) == MagickFalse) { mean_image=DestroyImage(mean_image); return((Image *) NULL); } status=MagickTrue; progress=0; image_view=AcquireVirtualCacheView(image,exception); pixel_view=AcquireVirtualCacheView(image,exception); mean_view=AcquireAuthenticCacheView(mean_image,exception); #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp parallel for schedule(static,4) shared(status,progress) \ magick_threads(mean_image,mean_image,mean_image->rows,1) #endif for (y=0; y < (ssize_t) mean_image->rows; y++) { register const Quantum *magick_restrict p; register Quantum *magick_restrict q; register ssize_t x; if (status == MagickFalse) continue; p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception); q=GetCacheViewAuthenticPixels(mean_view,0,y,mean_image->columns,1, exception); if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL)) { status=MagickFalse; continue; } for (x=0; x < (ssize_t) mean_image->columns; x++) { PixelInfo mean_pixel, previous_pixel; PointInfo mean_location, previous_location; register ssize_t i; GetPixelInfo(image,&mean_pixel); GetPixelInfoPixel(image,p,&mean_pixel); mean_location.x=(double) x; mean_location.y=(double) y; for (i=0; i < MaxMeanShiftIterations; i++) { double distance, gamma; PixelInfo sum_pixel; PointInfo sum_location; ssize_t count, v; sum_location.x=0.0; sum_location.y=0.0; GetPixelInfo(image,&sum_pixel); previous_location=mean_location; previous_pixel=mean_pixel; count=0; for (v=(-((ssize_t) height/2)); v <= (((ssize_t) height/2)); v++) { ssize_t u; for (u=(-((ssize_t) width/2)); u <= (((ssize_t) width/2)); u++) { if ((v*v+u*u) <= (ssize_t) ((width/2)*(height/2))) { PixelInfo pixel; status=GetOneCacheViewVirtualPixelInfo(pixel_view,(ssize_t) MagickRound(mean_location.x+u),(ssize_t) MagickRound( mean_location.y+v),&pixel,exception); distance=(mean_pixel.red-pixel.red)*(mean_pixel.red-pixel.red)+ (mean_pixel.green-pixel.green)*(mean_pixel.green-pixel.green)+ (mean_pixel.blue-pixel.blue)*(mean_pixel.blue-pixel.blue); if (distance <= (color_distance*color_distance)) { sum_location.x+=mean_location.x+u; sum_location.y+=mean_location.y+v; sum_pixel.red+=pixel.red; sum_pixel.green+=pixel.green; sum_pixel.blue+=pixel.blue; sum_pixel.alpha+=pixel.alpha; count++; } } } } gamma=1.0/count; mean_location.x=gamma*sum_location.x; mean_location.y=gamma*sum_location.y; mean_pixel.red=gamma*sum_pixel.red; mean_pixel.green=gamma*sum_pixel.green; mean_pixel.blue=gamma*sum_pixel.blue; mean_pixel.alpha=gamma*sum_pixel.alpha; distance=(mean_location.x-previous_location.x)* (mean_location.x-previous_location.x)+ (mean_location.y-previous_location.y)* (mean_location.y-previous_location.y)+ 255.0*QuantumScale*(mean_pixel.red-previous_pixel.red)* 255.0*QuantumScale*(mean_pixel.red-previous_pixel.red)+ 255.0*QuantumScale*(mean_pixel.green-previous_pixel.green)* 255.0*QuantumScale*(mean_pixel.green-previous_pixel.green)+ 255.0*QuantumScale*(mean_pixel.blue-previous_pixel.blue)* 255.0*QuantumScale*(mean_pixel.blue-previous_pixel.blue); if (distance <= 3.0) break; } SetPixelRed(mean_image,ClampToQuantum(mean_pixel.red),q); SetPixelGreen(mean_image,ClampToQuantum(mean_pixel.green),q); SetPixelBlue(mean_image,ClampToQuantum(mean_pixel.blue),q); SetPixelAlpha(mean_image,ClampToQuantum(mean_pixel.alpha),q); p+=GetPixelChannels(image); q+=GetPixelChannels(mean_image); } if (SyncCacheViewAuthenticPixels(mean_view,exception) == MagickFalse) status=MagickFalse; if (image->progress_monitor != (MagickProgressMonitor) NULL) { MagickBooleanType proceed; #if defined(MAGICKCORE_OPENMP_SUPPORT) #pragma omp critical (MagickCore_MeanShiftImage) #endif proceed=SetImageProgress(image,MeanShiftImageTag,progress++, image->rows); if (proceed == MagickFalse) status=MagickFalse; } } mean_view=DestroyCacheView(mean_view); pixel_view=DestroyCacheView(pixel_view); image_view=DestroyCacheView(image_view); return(mean_image); }