/* %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % % % % % 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 1999-2014 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/property.h" #include "MagickCore/animate.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/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/memory_.h" #include "MagickCore/module.h" #include "MagickCore/monitor.h" #include "MagickCore/monitor-private.h" #include "MagickCore/option.h" #include "MagickCore/paint.h" #include "MagickCore/pixel-accessor.h" #include "MagickCore/profile.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" /* %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % % % % % 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 ssize_t MagickAbsoluteValue(const ssize_t x) { if (x < 0) return(-x); return(x); } 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; size_t length; ssize_t y; unsigned int number_grays; assert(image != (Image *) NULL); assert(image->signature == MagickSignature); if (image->debug != MagickFalse) (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename); if ((image->columns < (distance+1)) || (image->rows < (distance+1))) return((ChannelFeatures *) NULL); length=CompositeChannels+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 (y=0; y < (ssize_t) image->rows; y++) { register const Quantum *restrict p; register ssize_t x; if (status == MagickFalse) continue; p=GetCacheViewVirtualPixels(image_view,0,y,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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 (y=0; y < (ssize_t) image->rows; y++) { register const Quantum *restrict p; register ssize_t x; ssize_t i, offset, u, v; if (status == MagickFalse) continue; p=GetCacheViewVirtualPixels(image_view,-(ssize_t) distance,y,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 == BlendPixelTrait) { 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) { 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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*(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*(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*(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*(entropy_xy2.direction[i].black- entropy_xy.direction[i].black))))); if (image->alpha_trait == BlendPixelTrait) channel_features[AlphaPixelChannel].measure_of_correlation_2[i]= (sqrt(fabs(1.0-exp(-2.0*(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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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 == BlendPixelTrait) 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); }