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I've around $500$ binary (black and white) images, of which I attach $2$ samples. I'm working on a machine learning problem of classifying images like them. I'd like to know what image features I can use that'd be very distinct for distinct images of this type. I tried HOG features, but the difficulty is they're very high dimensional (even for a $64 \times 64$ image, the HOG feature dimension is $1764$), so the models will overfit. Hence the question. Thanks!

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  • $\begingroup$ I'm not that familiar with machine learning, but from what material I've read/seen and my intuition I'd say a convolutional neural network with subsampling layers should work well here. $\endgroup$ – orlp Jul 22 '17 at 5:47
  • $\begingroup$ Hu / Zernike moments? Why don't you preprocess your images with skeletonization or other techniques? $\endgroup$ – Evil Jul 22 '17 at 17:02

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