different features such as Zernike moment (1 feature) , Hu's Invariant Moments (7 feature) , chip histogram (6 features) , texture features using GLCM (13 features) , Haralick texture features (14 features) , GLCM Features4 (22 features) , grey level run length matrix (GLRLM) (7 features) , modified Haussdorf FD (3 features) , grey level difference method (GLDM) (4 features)
In MATLAB you can solve your problem as the following links
Zernike moment https://ww2.mathworks.cn/matlabcentral/fileexchange/38900-zernike-moments?requestedDomain=en
Hu's Invariant Moments https://ww2.mathworks.cn/matlabcentral/fileexchange/52259-hu-s-invariant-moments?requestedDomain=en
chip histogram https://ww2.mathworks.cn/help/images/ref/imhist.html?requestedDomain=en
texture features using GLCM https://ww2.mathworks.cn/matlabcentral/fileexchange/22187-glcm-texture-features?requestedDomain=en
Haralick texture features https://ww2.mathworks.cn/matlabcentral/fileexchange/58769-haralicktexturefeatures?requestedDomain=en
GLCM Features4 https://ww2.mathworks.cn/matlabcentral/fileexchange/56661-glcm_features-glcm?requestedDomain=en
grey level run length matrix (GLRLM) https://ww2.mathworks.cn/matlabcentral/fileexchange/17482-gray-level-run-length-matrix-toolbox?requestedDomain=en
modified Haussdorf FD https://ww2.mathworks.cn/matlabcentral/fileexchange/29968-modifiedhausdorff-distance?requestedDomain=en
grey level difference method https://ww2.mathworks.cn/matlabcentral/fileexchange/25057-texture-feature-extraction-gldm?requestedDomain=en
You can find a lot of these features in scikit-image library, the other libraries to look for are certainly OpenCV. In fact - after a quick check - I think you can find most of the features you are interested in in those 2 python libraries. You might also have a look at the classical SciPy library.
For some specifics, there's also PyHausdorff module available on github (https://github.com/mavillan/py-hausdorff).
please see the following link
https://www.kaggle.com/pmarcelino/data-analysis-and-feature-extraction-with-python
In MATLAB you can solve your problem as the following links
Zernike moment https://ww2.mathworks.cn/matlabcentral/fileexchange/38900-zernike-moments?requestedDomain=en
Hu's Invariant Moments https://ww2.mathworks.cn/matlabcentral/fileexchange/52259-hu-s-invariant-moments?requestedDomain=en
chip histogram https://ww2.mathworks.cn/help/images/ref/imhist.html?requestedDomain=en
texture features using GLCM https://ww2.mathworks.cn/matlabcentral/fileexchange/22187-glcm-texture-features?requestedDomain=en
Haralick texture features https://ww2.mathworks.cn/matlabcentral/fileexchange/58769-haralicktexturefeatures?requestedDomain=en
GLCM Features4 https://ww2.mathworks.cn/matlabcentral/fileexchange/56661-glcm_features-glcm?requestedDomain=en
grey level run length matrix (GLRLM) https://ww2.mathworks.cn/matlabcentral/fileexchange/17482-gray-level-run-length-matrix-toolbox?requestedDomain=en
modified Haussdorf FD https://ww2.mathworks.cn/matlabcentral/fileexchange/29968-modifiedhausdorff-distance?requestedDomain=en
grey level difference method https://ww2.mathworks.cn/matlabcentral/fileexchange/25057-texture-feature-extraction-gldm?requestedDomain=en
https://towardsdatascience.com/feature-selection-techniques-in-machine-learning-with-python-f24e7da3f36e
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