Abstract:

Based on the nonparametric feature analysis (NFA) method, the paper proposed a modular NFA algorithm and applied it on face recognition. Firstly, the modular NFA algorithm divides the original images into modular subimages. Secondly, the NFA method is employed to extract the features of the modular subimages. There are two advantages: 1) local feature of the images can be extracted efficiently, and it has outstanding effect for the images that have large variations in facial expression and illumination; (2) Singular value decomposition of matrix may be avoided in the process of feature extraction, which is simpler than that of other technologies such as NFA. Meanwhile, it overcomes the small sample size problem. Moreover, NFA is a special case of modular NFA. Experimental results on ORL and YALE face databases show that the performance of modular NFA is superior to NFA and modular NSA.              

Key words: face recognition;nonparametric feature analysis;modular NFA