Face Recognition Algorithm Using Muti-direction Markov Stationary Features and Adjacent Pixel Intensity Difference Quantization Histogram

We have proposed a robust face recognition algorithm using adjacent pixel intensity difference quantization (APIDQ) histogram combined with Markov Stationary Features (MSF) so as to add spatial structure information to histogram features in our previous work. We named the new histogram feature as MSF-DQ feature. In this paper, we extend original MSF to multi-direction MSF by generating co-occurrence matrices with orientations of 0, 45, 90, 135 degrees, and then extract corresponding MSF-DQ features for every direction. Publicly available AT&T database of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions, is used to evaluate the performance of the proposed algorithm. Experimental results show face recognition using proposed multi-direction MSF-DQ features is more efficient compared with the original algorithm. Keywords-Face recognition; Adjacent pixel intensity difference quantization (APIDQ); Markov stationary feature (MSF); Multi-direction; Histogram feature.

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