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How to use local binary pattern to extract features?
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I am new to MATLAB. Kindly help me how to use local binary pattern to extract features from images?
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Image Analyst
el 17 de Dic. de 2015
See my attached demo to compute the LBP. It doesn't extract any features from it - it merely computes it. Somehow you'd then have to analyze the LBP to get some feature that you're interested in.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/172366/image.jpeg)
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Image Analyst
el 17 de Dic. de 2015
I don't know what the current best approach is. And it might depend on your field of view and how much contrast the lips have to the face. I refer you to the latest literature on it because I am not a researcher in that field of image processing: http://www.visionbib.com/bibliography/contentspeople.html#Face%20Recognition,%20Detection,%20Tracking,%20Gesture%20Recognition,%20Fingerprints,%20Biometrics
Stefan Karlsson
el 17 de Dic. de 2015
Last I checked, LBPs where the best performing low-level features for facial, and facial parts tracking... as far as the Viola-jones cascaded ada-boost framework goes. I am not very updated though. The LBP version found in OpenCV out-performs the previous version in both efficiency and accuracy. The old version, however, was just Haar-like features, so this is not suprsing. For state of the art today, I guess deep-learning should, or will soon dominate here as well. That approach leaves feature selection in the hands of the framework.
When i used LBPs in OpenCV, the documentation mentioned their rotation invariant properties, but the actual implementation was not rotation invariant. Perhaps this has changed too now. Rotation invariance for anything with facial tracking is usually important. Scale invariance is built-into the VJ classifier, so you dont need that in the features.... good luck!
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