Abstract
U-face concept was first proposed to improve the rate of face recognition. U-face is a face recognition normalization model. U-face removes background, hair, and other factors that are not conducive to face recognition; retain only the focus of the face region. In the case of necessary human face images were rotated and histogram normalized. And then describes the Kernel Principal Component Analysis (KPCA) face recognition method. Using KPCA and Principal Component Analysis (PCA) face recognition methods on U-face simulation, simulation results show that the U-face improves the recognition rate.
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