A face recognition method based on modular PCA and SVD
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    Abstract:

    In order to solve the problem that modular PCA method is sensitive to translation, rotation and other geometric transform, a face recognition method based on modular PCA and singular value decomposition (SVD) is proposed. The PCA features of sub image and SVD features are extracted respectively. The distance measure that fuses information of modular PCA and SVD is obtained. Minimum distance classifier is used to face recognition. Experimental results on ORL human face database show that the proposed method can obtain higher recognition rate.

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印勇,何文娟,郭之强,郭攀,徐亦达.分块PCA和奇异值分解相结合的人脸识别算法[J].重庆大学学报,2012,35(8):134~138

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  • Online: September 04,2012
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