Two-dimensional neighborhood preserving discriminant analysis for face recognition
Guanming Lu, Jiakuo Zuo · 2010 Sixth International Conference on Natural Computation · 2010
In this paper, we propose an innovative feature extraction algorithm named two-dimensional neighborhood preserving discriminant analysis (2DNPDA), which directly extracts feature from image matrix. The proposed algorithm considers both the neighborhood structure of the samples and the discriminant information of different classes. Experimental results on ORL and Yale face databases show that 2DNPDA can attain better recognition rate than PCA, LDA, MMC, 2DPCA, 2DLDA and LPP.