How to calculate the contrast energy, entropy of a ROI(Region of interest) of an image using GLCM feature extractactions method?

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I need to extract GLCM features like energy entropy contrast among others of the REGION OF INTEREST ONLY excluding the black background,i managed to extract those features for the entire image but i only need them for the region of interest knowing that everything else will be black
% Loop over all GLCMs
for k = 1:nglcm
currentGLCM = glcm(:,:,k);
glcmMean(k) = mean2(currentGLCM);
% For symmetric GLCMs, uX = uY
uX(k) = sum(I.*currentGLCM(sub));
uY(k) = sum(J.*currentGLCM(sub));
sX(k) = sum((I-uX(k)).^2.*currentGLCM(sub));
sY(k) = sum((J-uY(k)).^2.*currentGLCM(sub));
out.contrast(k) = sum(abs(I-J).^2.*currentGLCM(sub)); %OK
out.dissimilarity(k) = sum(abs(I - J).*currentGLCM(sub)); %OK = sum(currentGLCM(sub).^2); % OK
out.entropy(k) = -nansum(currentGLCM(sub).*log(currentGLCM(sub))); %OK
out.inverseDifference(k) = sum(currentGLCM(sub)./( 1 + abs(I-J) )); %OK
out.homogeneity(k) = sum(currentGLCM(sub)./( 1 + (I - J).^2)); %OK
Ragini Gaikwad
Ragini Gaikwad on 13 May 2021
Guys, please help me on this. I want to take 10 images form my image database, read them, index them, find grey level and histogram. make bin to size 15. calculate feature vector of each image. calulate ED or MSE.
please help me with this.

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Answers (3)

Phuong Nguyen
Phuong Nguyen on 3 Apr 2020
Did you solve this problem? I am having the same problem with you and cant get over it. If you done, could you please teach me? Thank you.
  1 Comment
Binu on 8 May 2020
Force all pixel values outside your region of interest as a 'NaN'. The graycomatrix methods by default ignores any pixel pairs having a 'NaN' value.

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Image Analyst
Image Analyst on 5 Jun 2017
graycoprops() returns 4 measurements. Will that do?

Binu on 4 Aug 2017
The graycomatrix function has a '*GrayLimits*' argument where you can specify a two-element vector [low high] which is used for scaling the image and creating NumLevels. Grayscale values less than or equal to low are scaled to 1. You could set that yours to [0.1 1] for your case.

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