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28 March 2005 Most information feature extraction (MIFE) approach for face recognition
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Abstract
We present a MIFE (Most Information Feature Extraction) approach, which extract as abundant as possible information for the face classification task. In the MIFE approach, a facial image is separated into sub-regions and each sub-region makes individual’s contribution for performing face recognition. Specifically, each sub-region is subjected to a sub-region based adaptive gamma (SadaGamma) correction or sub-region based histogram equalization (SHE) in order to account for different illuminations and expressions. Experiment results show that the proposed SadaGamma/SHE correction approach provides an efficient delighting solution for face recognition. MIFE and SadaGamma/SHE correction together achieves lower error ratio in face recognition under different illumination and expression.
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Jiali Zhao, Haibing Ren, Haitao Wang, and Seokcheol Kee "Most information feature extraction (MIFE) approach for face recognition", Proc. SPIE 5779, Biometric Technology for Human Identification II, (28 March 2005); https://doi.org/10.1117/12.601880
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