Compute texture for small parts of the image
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MatlabUser
am 21 Dez. 2020
Kommentiert: MatlabUser
am 23 Dez. 2020
Hello,
I would like to ask about how to computing the texture of a part of the image efficiently, i.e., I applied superpixel segmentation (SLIC) on an image to get smaller homogenous regions, how to compute the texture for each superpixel efficiently (e.g., fast execution)?
any help will be appreciated,
best regards,
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Image Analyst
am 21 Dez. 2020
Depends on how you define texture. One way is to use the labeled image from superpixels() to get the mean intensity of the StDev image
windowSize = 9; % Whatever...
stDevImage = stdfilt(grayImage, ones(windowSize)); % A local standard deviation.
% Get the standard deviation averaged over each superpixel region.
props = regionprops(labeledImage, stDevImage, 'MeanIntensity');
for k = 1 : length(props)
fprintf('The mean standard deviation in superpixel #%d of %d is %f.\n', ...
k, length(props), props(k).MeanIntensity)
end
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Image Analyst
am 23 Dez. 2020
No, I don't believe so, unless the help says superpizel() returns a texture. It returns a labeled image which you can then use with a texture image and regionprops() to determine texture in each superpixel region.
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