Robust face recognition based on illumination invariant in nonsubsampled contourlet transform domain

Authors:
Yong Cheng;Yingkun Hou;Chunxia Zhao;Zuoyong Li;Yong Hu;Cailing Wang
Affiliations:
School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China and School of Communication Engineering, Nanjing Institute of Technology, Nanjing 211 ...;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China and School of Information Science and Technology, Taishan University, Taian, Shandong ...;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China and Department of Computer Science, Minjiang University, Fuzhou 350108, China;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China
Venue:
Neurocomputing
Year:
2010

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Abstract

In order to alleviate the effect of illumination variations on face recognition, a novel face recognition algorithm based on illumination invariant in nonsubsampled contourlet transform (NSCT) domain is proposed. The algorithm first performs logarithm transform on original face images under various illumination conditions, which changes multiplicative illumination model into an additive one. Then NSCT is used to decompose the logarithm transformed images. After that, adaptive NormalShrink is applied to each directional subband of NSCT for illumination invariant extraction. Experimental results on the Yale B, the extended Yale and the CMU PIE face databases show that the proposed algorithm can effectively alleviate the effect of illumination on face recognition.