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ComputeCMFeatures.m
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ComputeCMFeatures.m
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%%
% Written by Humayun Irshad ([email protected])
% Feb 2015
%%
function [ GLCMFeatures ] = ComputeCMFeatures( RGB, BW, NoOfChannels, GrayLevels, FeaturesPath, ImageName)
%ComputeCMFeatures compute Co-occurrence features in seven color
%channels (Red, Green, Blue, HSV(V), Lab(L), H&E(H) and BR
%
if(nargin < 4)
GrayLevels = 64;
end
myFcn=@(x)graycomatrix(x,'Offset',[1 0;0 1;1 1;-1 1],'Symmetric',...
true, 'NumLevels', GrayLevels);
[x,y]=size(BW);
[L,num] = bwlabel(BW);
bb = regionprops(L,'BoundingBox');
bb = floor(cat(1,bb.BoundingBox));
GS_or_RGB = size(RGB,3);
if (GS_or_RGB == 1)
RGB = uint8(256*mat2gray(RGB));
GLCMFeatures = struct( ...
'Autocorrelation_GS',0, 'CorrelationP_GS',0, 'Contrast_GS',0, ...
'ClusterShade_GS',0, 'ClusterProminence_GS',0, 'Energy_GS',0, ...
'Entropy_GS',0, 'HomogeneityP_GS',0, 'InverseDiffNormalized_GS',0, ...
'InverseDiffMomentNormalized_GS',0, 'Dissimilarity_GS',0, ...
'MaxProbability_GS',0, 'InfoMeasureCorr1_GS',0, ...
'InformeasureCorr2_GS',0);
for i = 1:num
obj=RGB;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_GS(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_GS(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_GS(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_GS(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_GS(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_GS(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_GS(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_GS(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_GS(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_GS(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_GS(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_GS(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_GS(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_GS(i,1) = mean(glcmFeatures.inf2h);
end
elseif(GS_or_RGB == 3)
if(NoOfChannels == 4 && isnumeric(NoOfChannels))
GLCMFeatures = struct( ...
'Autocorrelation_R',0, 'CorrelationP_R',0, 'Contrast_R',0, ...
'ClusterShade_R',0, 'ClusterProminence_R',0, 'Energy_R',0, ...
'Entropy_R',0, 'HomogeneityP_R',0, 'InverseDiffNormalized_R',0, ...
'InverseDiffMomentNormalized_R',0, 'Dissimilarity_R',0, ...
'MaxProbability_R',0, 'InfoMeasureCorr1_R',0, ...
'InformeasureCorr2_R',0, ...
'Autocorrelation_V',0, 'CorrelationP_V',0, 'Contrast_V',0, ...
'ClusterShade_V',0, 'ClusterProminence_V',0, 'Energy_V',0, ...
'Entropy_V',0, 'HomogeneityP_V',0, 'InverseDiffNormalized_V',0, ...
'InverseDiffMomentNormalized_V',0, 'Dissimilarity_V',0, ...
'MaxProbability_V',0, 'InfoMeasureCorr1_V',0, ...
'InformeasureCorr2_V',0, ...
'Autocorrelation_L',0, 'CorrelationP_L',0, 'Contrast_L',0, ...
'ClusterShade_L',0, 'ClusterProminence_L',0, 'Energy_L',0, ...
'Entropy_L',0, 'HomogeneityP_L',0, 'InverseDiffNormalized_L',0, ...
'InverseDiffMomentNormalized_L',0, 'Dissimilarity_L',0, ...
'MaxProbability_L',0, 'InfoMeasureCorr1_L',0, ...
'InformeasureCorr2_L',0, ...
'Autocorrelation_H',0, 'CorrelationP_H',0, 'Contrast_H',0, ...
'ClusterShade_H',0, 'ClusterProminence_H',0, 'Energy_H',0, ...
'Entropy_H',0, 'HomogeneityP_H',0, 'InverseDiffNormalized_H',0, ...
'InverseDiffMomentNormalized_H',0, 'Dissimilarity_H',0, ...
'MaxProbability_H',0, 'InfoMeasureCorr1_H',0, ...
'InformeasureCorr2_H',0);
%% 1 - Red Channel
channel = RGB(:,:,1);
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_R(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_R(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_R(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_R(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_R(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_R(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_R(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_R(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_R(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_R(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_R(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_R(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_R(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_R(i,1) = mean(glcmFeatures.inf2h);
end
%% 2 - V (HSV) Channel
channel = rgb2hsv(RGB);
channel = uint8(GrayLevels*mat2gray(channel(:,:,3)));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_V(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_V(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_V(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_V(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_V(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_V(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_V(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_V(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_V(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_V(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_V(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_V(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_V(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_V(i,1) = mean(glcmFeatures.inf2h);
end
%% 3 - L (Lab) Channel
channel = rgb2lab(RGB);
channel = uint8(GrayLevels*mat2gray(channel(:,:,1)));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_L(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_L(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_L(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_L(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_L(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_L(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_L(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_L(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_L(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_L(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_L(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_L(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_L(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_L(i,1) = mean(glcmFeatures.inf2h);
end
%% 4 - H (H&E) Channel
%[ A1, A2, A3, A4, A5, A6, A7, A8 ] = colordeconv( RGB, 2 );
%[ DCH, H, E, R, M] = Deconvolve( RGB ); % Ruifrok Method (Adnan)
[ channel, ~, ~] = colordeconv2( RGB, 'PSL' ); % IPAL Method
channel = uint8(GrayLevels*mat2gray(channel));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_H(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_H(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_H(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_H(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_H(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_H(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_H(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_H(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_H(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_H(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_H(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_H(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_H(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_H(i,1) = mean(glcmFeatures.inf2h);
end
elseif(NoOfChannels == 7 && isnumeric(NoOfChannels))
GLCMFeatures = struct( ...
'Autocorrelation_R',0, 'CorrelationP_R',0, 'Contrast_R',0, ...
'ClusterShade_R',0, 'ClusterProminence_R',0, 'Energy_R',0, ...
'Entropy_R',0, 'HomogeneityP_R',0, 'InverseDiffNormalized_R',0, ...
'InverseDiffMomentNormalized_R',0, 'Dissimilarity_R',0, ...
'MaxProbability_R',0, 'InfoMeasureCorr1_R',0, ...
'InformeasureCorr2_R',0, ...
'Autocorrelation_G',0, 'CorrelationP_G',0, 'Contrast_G',0, ...
'ClusterShade_G',0, 'ClusterProminence_G',0, 'Energy_G',0, ...
'Entropy_G',0, 'HomogeneityP_G',0, 'InverseDiffNormalized_G',0, ...
'InverseDiffMomentNormalized_G',0, 'Dissimilarity_G',0, ...
'MaxProbability_G',0, 'InfoMeasureCorr1_G',0, ...
'InformeasureCorr2_G',0, ...
'Autocorrelation_B',0, 'CorrelationP_B',0, 'Contrast_B',0, ...
'ClusterShade_B',0, 'ClusterProminence_B',0, 'Energy_B',0, ...
'Entropy_B',0, 'HomogeneityP_B',0, 'InverseDiffNormalized_B',0, ...
'InverseDiffMomentNormalized_B',0, 'Dissimilarity_B',0, ...
'MaxProbability_B',0, 'InfoMeasureCorr1_B',0, ...
'InformeasureCorr2_B',0, ...
'Autocorrelation_V',0, 'CorrelationP_V',0, 'Contrast_V',0, ...
'ClusterShade_V',0, 'ClusterProminence_V',0, 'Energy_V',0, ...
'Entropy_V',0, 'HomogeneityP_V',0, 'InverseDiffNormalized_V',0, ...
'InverseDiffMomentNormalized_V',0, 'Dissimilarity_V',0, ...
'MaxProbability_V',0, 'InfoMeasureCorr1_V',0, ...
'InformeasureCorr2_V',0, ...
'Autocorrelation_L',0, 'CorrelationP_L',0, 'Contrast_L',0, ...
'ClusterShade_L',0, 'ClusterProminence_L',0, 'Energy_L',0, ...
'Entropy_L',0, 'HomogeneityP_L',0, 'InverseDiffNormalized_L',0, ...
'InverseDiffMomentNormalized_L',0, 'Dissimilarity_L',0, ...
'MaxProbability_L',0, 'InfoMeasureCorr1_L',0, ...
'InformeasureCorr2_L',0, ...
'Autocorrelation_H',0, 'CorrelationP_H',0, 'Contrast_H',0, ...
'ClusterShade_H',0, 'ClusterProminence_H',0, 'Energy_H',0, ...
'Entropy_H',0, 'HomogeneityP_H',0, 'InverseDiffNormalized_H',0, ...
'InverseDiffMomentNormalized_H',0, 'Dissimilarity_H',0, ...
'MaxProbability_H',0, 'InfoMeasureCorr1_H',0, ...
'InformeasureCorr2_H',0, ...
'Autocorrelation_Br',0, 'CorrelationP_Br',0, 'Contrast_Br',0, ...
'ClusterShade_Br',0, 'ClusterProminence_Br',0, 'Energy_Br',0, ...
'Entropy_Br',0, 'HomogeneityP_Br',0, 'InverseDiffNormalized_Br',0, ...
'InverseDiffMomentNormalized_Br',0, 'Dissimilarity_Br',0, ...
'MaxProbability_Br',0, 'InfoMeasureCorr1_Br',0, ...
'InformeasureCorr2_Br',0 );
%% 1 - Red Channel
channel = RGB(:,:,1);
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_R(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_R(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_R(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_R(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_R(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_R(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_R(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_R(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_R(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_R(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_R(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_R(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_R(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_R(i,1) = mean(glcmFeatures.inf2h);
end
%% 2 - Green Channel
channel = RGB(:,:,2);
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_G(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_G(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_G(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_G(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_G(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_G(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_G(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_G(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_G(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_G(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_G(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_G(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_G(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_G(i,1) = mean(glcmFeatures.inf2h);
end
%% 3 - Blue Channel
channel = RGB(:,:,3);
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_B(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_B(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_B(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_B(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_B(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_B(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_B(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_B(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_B(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_B(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_B(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_B(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_B(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_B(i,1) = mean(glcmFeatures.inf2h);
end
%% 4 - V (HSV) Channel
channel = rgb2hsv(RGB);
channel = uint8(GrayLevels*mat2gray(channel(:,:,3)));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_V(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_V(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_V(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_V(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_V(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_V(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_V(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_V(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_V(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_V(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_V(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_V(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_V(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_V(i,1) = mean(glcmFeatures.inf2h);
end
%% 5 - L (Lab) Channel
channel = rgb2lab(RGB);
channel = uint8(GrayLevels*mat2gray(channel(:,:,1)));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_L(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_L(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_L(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_L(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_L(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_L(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_L(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_L(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_L(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_L(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_L(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_L(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_L(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_L(i,1) = mean(glcmFeatures.inf2h);
end
%% 6 - H (H&E) Channel
%[ A1, A2, A3, A4, A5, A6, A7, A8 ] = colordeconv( RGB, 2 );
%[ DCH, H, E, R, M] = Deconvolve( RGB ); % Ruifrok Method (Adnan)
[ channel, ~, ~] = colordeconv2( RGB, 'PSL' ); % IPAL Method
channel = uint8(GrayLevels*mat2gray(channel));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_H(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_H(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_H(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_H(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_H(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_H(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_H(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_H(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_H(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_H(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_H(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_H(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_H(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_H(i,1) = mean(glcmFeatures.inf2h);
end
%% 7 - BlueRatio Image
channel= uint8(GrayLevels*mat2gray(ComputeBlueRatio(RGB)));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_Br(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_Br(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_Br(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_Br(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_Br(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_Br(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_Br(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_Br(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_Br(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_Br(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_Br(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_Br(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_Br(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_Br(i,1) = mean(glcmFeatures.inf2h);
end
elseif(NoOfChannels == 'R' && ~isnumeric(NoOfChannels))
GLCMFeatures = struct( ...
'Autocorrelation_R',0, 'CorrelationP_R',0, 'Contrast_R',0, ...
'ClusterShade_R',0, 'ClusterProminence_R',0, 'Energy_R',0, ...
'Entropy_R',0, 'HomogeneityP_R',0, 'InverseDiffNormalized_R',0, ...
'InverseDiffMomentNormalized_R',0, 'Dissimilarity_R',0, ...
'MaxProbability_R',0, 'InfoMeasureCorr1_R',0, ...
'InformeasureCorr2_R',0);
%% 1 - Red Channel
channel = RGB(:,:,1);
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_R(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_R(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_R(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_R(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_R(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_R(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_R(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_R(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_R(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_R(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_R(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_R(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_R(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_R(i,1) = mean(glcmFeatures.inf2h);
end
elseif(NoOfChannels == 'G' && ~isnumeric(NoOfChannels))
GLCMFeatures = struct( ...
'Autocorrelation_G',0, 'CorrelationP_G',0, 'Contrast_G',0, ...
'ClusterShade_G',0, 'ClusterProminence_G',0, 'Energy_G',0, ...
'Entropy_G',0, 'HomogeneityP_G',0, 'InverseDiffNormalized_G',0, ...
'InverseDiffMomentNormalized_G',0, 'Dissimilarity_G',0, ...
'MaxProbability_G',0, 'InfoMeasureCorr1_G',0, ...
'InformeasureCorr2_G',0);
channel = RGB(:,:,2);
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_G(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_G(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_G(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_G(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_G(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_G(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_G(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_G(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_G(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_G(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_G(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_G(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_G(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_G(i,1) = mean(glcmFeatures.inf2h);
end
elseif(NoOfChannels == 'B' && ~isnumeric(NoOfChannels))
GLCMFeatures = struct( ...
'Autocorrelation_B',0, 'CorrelationP_B',0, 'Contrast_B',0, ...
'ClusterShade_B',0, 'ClusterProminence_B',0, 'Energy_B',0, ...
'Entropy_B',0, 'HomogeneityP_B',0, 'InverseDiffNormalized_B',0, ...
'InverseDiffMomentNormalized_B',0, 'Dissimilarity_B',0, ...
'MaxProbability_B',0, 'InfoMeasureCorr1_B',0, ...
'InformeasureCorr2_B',0);
channel = RGB(:,:,3);
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_B(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_B(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_B(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_B(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_B(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_B(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_B(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_B(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_B(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_B(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_B(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_B(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_B(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_B(i,1) = mean(glcmFeatures.inf2h);
end
elseif(NoOfChannels == 'V' && ~isnumeric(NoOfChannels))
GLCMFeatures = struct( ...
'Autocorrelation_V',0, 'CorrelationP_V',0, 'Contrast_V',0, ...
'ClusterShade_V',0, 'ClusterProminence_V',0, 'Energy_V',0, ...
'Entropy_V',0, 'HomogeneityP_V',0, 'InverseDiffNormalized_V',0, ...
'InverseDiffMomentNormalized_V',0, 'Dissimilarity_V',0, ...
'MaxProbability_V',0, 'InfoMeasureCorr1_V',0, ...
'InformeasureCorr2_V',0);
channel = rgb2hsv(RGB);
channel = uint8(GrayLevels*mat2gray(channel(:,:,3)));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_V(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_V(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_V(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_V(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_V(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_V(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_V(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_V(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_V(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_V(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_V(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_V(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_V(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_V(i,1) = mean(glcmFeatures.inf2h);
end
elseif(NoOfChannels == 'L' && ~isnumeric(NoOfChannels))
GLCMFeatures = struct( ...
'Autocorrelation_L',0, 'CorrelationP_L',0, 'Contrast_L',0, ...
'ClusterShade_L',0, 'ClusterProminence_L',0, 'Energy_L',0, ...
'Entropy_L',0, 'HomogeneityP_L',0, 'InverseDiffNormalized_L',0, ...
'InverseDiffMomentNormalized_L',0, 'Dissimilarity_L',0, ...
'MaxProbability_L',0, 'InfoMeasureCorr1_L',0, ...
'InformeasureCorr2_L',0);
channel = rgb2lab(RGB);
channel = uint8(GrayLevels*mat2gray(channel(:,:,1)));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_L(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_L(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_L(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_L(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_L(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_L(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_L(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_L(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_L(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_L(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_L(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_L(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_L(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_L(i,1) = mean(glcmFeatures.inf2h);
end
elseif(NoOfChannels == 'H' && ~isnumeric(NoOfChannels))
GLCMFeatures = struct( ...
'Autocorrelation_H',0, 'CorrelationP_H',0, 'Contrast_H',0, ...
'ClusterShade_H',0, 'ClusterProminence_H',0, 'Energy_H',0, ...
'Entropy_H',0, 'HomogeneityP_H',0, 'InverseDiffNormalized_H',0, ...
'InverseDiffMomentNormalized_H',0, 'Dissimilarity_H',0, ...
'MaxProbability_H',0, 'InfoMeasureCorr1_H',0, ...
'InformeasureCorr2_H',0);
%[ A1, A2, A3, A4, A5, A6, A7, A8 ] = colordeconv( RGB, 2 );
%[ DCH, H, E, R, M] = Deconvolve( RGB ); % Ruifrok Method (Adnan)
[ channel, ~, ~] = colordeconv2( RGB, 'PSL' ); % IPAL Method
channel = uint8(GrayLevels*mat2gray(channel));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_H(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_H(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_H(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_H(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_H(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_H(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_H(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_H(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_H(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_H(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_H(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_H(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_H(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_H(i,1) = mean(glcmFeatures.inf2h);
end
elseif(strcmp(NoOfChannels,'BR') && ~isnumeric(NoOfChannels))
GLCMFeatures = struct( ...
'Autocorrelation_Br',0, 'CorrelationP_Br',0, 'Contrast_Br',0, ...
'ClusterShade_Br',0, 'ClusterProminence_Br',0, 'Energy_Br',0, ...
'Entropy_Br',0, 'HomogeneityP_Br',0, 'InverseDiffNormalized_Br',0, ...
'InverseDiffMomentNormalized_Br',0, 'Dissimilarity_Br',0, ...
'MaxProbability_Br',0, 'InfoMeasureCorr1_Br',0, ...
'InformeasureCorr2_Br',0 );
channel= uint8(GrayLevels*mat2gray(ComputeBlueRatio(RGB)));
for i = 1:num
obj=channel;
obj(~(L==i)) = NaN;
top_x = bb(i,2);
if(top_x<1)
top_x = 1;
end
top_y = bb(i,1);
if(top_y<1)
top_y = 1;
end
width = top_x+bb(i,4);
if(width > x)
width = x;
end
height = top_y+bb(i,3);
if(height > y)
height = y;
end
patch = obj(top_x:width,top_y:height);
glcm = myFcn(patch);
glcmFeatures = GLCM_Features(glcm,0);
GLCMFeatures.Autocorrelation_Br(i,1) = mean(glcmFeatures.autoc);
GLCMFeatures.CorrelationP_Br(i,1) = mean(glcmFeatures.corrp);
GLCMFeatures.Contrast_Br(i,1) = mean(glcmFeatures.contr);
GLCMFeatures.ClusterShade_Br(i,1) = mean(glcmFeatures.cshad);
GLCMFeatures.ClusterProminence_Br(i,1) = mean(glcmFeatures.cprom);
GLCMFeatures.Energy_Br(i,1) = mean(glcmFeatures.energ);
GLCMFeatures.Entropy_Br(i,1) = mean(glcmFeatures.entro);
GLCMFeatures.HomogeneityP_Br(i,1) = mean(glcmFeatures.homop);
GLCMFeatures.InverseDiffNormalized_Br(i,1) = mean(glcmFeatures.indnc);
GLCMFeatures.InverseDiffMomentNormalized_Br(i,1) = mean(glcmFeatures.idmnc);
GLCMFeatures.Dissimilarity_Br(i,1) = mean(glcmFeatures.dissi);
GLCMFeatures.MaxProbability_Br(i,1) = mean(glcmFeatures.maxpr);
GLCMFeatures.InfoMeasureCorr1_Br(i,1) = mean(glcmFeatures.inf1h);
GLCMFeatures.InformeasureCorr2_Br(i,1) = mean(glcmFeatures.inf2h);
end
end
end
if(nargin == 6)
struct2csv(GLCMFeatures, strcat(FeaturesPath, ImageName, '_CMFeatures.csv'));
end
GLCMFeatures = struct2table(GLCMFeatures);
end
% GLCMFeatures = struct( ...
% 'Autocorrelation_R',0, 'CorrelationP_R',0, 'Contrast_R',0, ...
% 'ClusterShade_R',0, 'ClusterProminence_R',0, 'Energy_R',0, ...
% 'Entropy_R',0, 'HomogeneityP_R',0, 'InverseDiffNormalized_R',0, ...
% 'InverseDiffMomentNormalized_R',0, 'Dissimilarity_R',0, ...
% 'MaxProbability_R',0, 'InfoMeasureCorr1_R',0, ...
% 'InformeasureCorr2_R',0, 'SumSqauresVariance_R',0, ...
% 'SumAverage_R',0, 'SumVariance_R',0, 'SumEntropy_R',0, ...
% 'DiffVariance_R',0, 'DiffEntropy_R',0, 'CorrelationM_R',0, ...
% 'HomogeneityM_R',0);
% RGB2 = RGB;
% RGB2(bb(i,2):bb(i,2)+bb(i,4),bb(i,1):bb(i,1)+bb(i,3), 1) = 0;
% RGB2(bb(i,2):bb(i,2)+bb(i,4),bb(i,1):bb(i,1)+bb(i,3), 2) = 255;
% RGB2(bb(i,2):bb(i,2)+bb(i,4),bb(i,1):bb(i,1)+bb(i,3), 3) = 0;
% figure, imshow(RGB2);
% obj=channel;
% obj(~(L==i)) = NaN;
% figure, imshow(obj);
% patch1 = RGB(bb(i,2):bb(i,2)+bb(i,4),bb(i,1):bb(i,1)+bb(i,3),:);
% patch2 = obj(bb(i,2):bb(i,2)+bb(i,4),bb(i,1):bb(i,1)+bb(i,3));
% figure, imshow(patch1);
% figure, imshow(patch2);