GLCM_Features(glcm)
This code is a vectorized version of the code submitted by Avinash Uppuluri.
The speedup (tested for the same subset of features) for a 200x200x4 GLCM matrix is about:
- 300x with respect to the original, non-vectorized version
- 10x with respect to the Avinash Uppuluri's own vectorized version
- 7x with respect to the vectorized implementation by Patrik Brynolfsson
NOTE: Formulas of features used in this implementation are based solely on the paper by Haralick et al.:
Haralick RM, Shanmuga K, Dinstein I.: Textural features for image classification. IEEE Trans Syst Man Cybern 3: 610-621, 1973
Other implementations may use slightly different formulations of "Sum of square: variance", "sum variance" and "difference variance". Always make sure which version is more suitable in the given case.
Cite As
Pawel Kleczek (2024). GLCM_Features(glcm) (https://www.mathworks.com/matlabcentral/fileexchange/56661-glcm_features-glcm), MATLAB Central File Exchange. Retrieved .
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- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis > Texture Analysis >
Tags
Acknowledgements
Inspired by: GLCM texture features
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Version | Published | Release Notes | |
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1.4.0.0 | Only changed the description |
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1.3.0.0 | - Fixed a bug related to hard-coded 3rd dimension of a GLCM matrix (was 4, now is size(GLCM,3)).
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1.2.0.0 | Fixed bug in computation of `t` for `svarh`: length(p_xplusy) gave incorrect results if `p_xplusy` was a 3x1x4 matrix (i.e. when GLCM matrix was a 2x2xk matrix). |
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1.1.0.0 | I've ensured that the current implementation of "Sum of square: variance", "sum variance" and "difference variance" conforms to the original paper by Haralick et al. |
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1.0.0.0 |