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杨万扣1, 吉善兵2, 任明武1, 杨静宇1(1.南京理工大学计算机学院,南京 210094;2.盐城市无线电管理处,盐城 224001)

摘 要
Face Extraction Based on Enhanced 2DPCA and Its Application to Face Recognition

YANG Wankou1, JI Shanbing2, REN Mingwu1, YANG Jingyu1(1.Computer Science Department, Nanjing University of Science and Techology, Nanjing 210094;2.Yancheng Radio Management Bureau, Yancheng 22400)

In this paper, a two-stage method of image feature extraction, called Enhanced two-dimensional principal component analysis (2DPCA), is proposed in this paper, which uses 2DPCA operated in the row direction and alternative 2DPCA operated in column direction. Enhanced 2DPCA can compress image in row and column direction. Enhanced 2DPCA needs fewer coefficients for image representation than 2DPCA does. The experimental results on the ORL and FERET database show that the Enhanced 2DPCA can work well and surpass two-directional two-dimensional principal component analysis((2D)2PCA).