Title
Robust face recognition based on illumination invariant in nonsubsampled contourlet transform domain
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.
Year
DOI
Venue
2010
10.1016/j.neucom.2010.01.012
Neurocomputing
Keywords
Field
DocType
original face image,face recognition,illumination invariant extraction,illumination invariant,nonsubsampled contourlet,illumination variation,robust face recognition,cmu pie face databases,multiplicative illumination model,proposed algorithm,various illumination condition,novel face recognition algorithm
Facial recognition system,Computer vision,Multiplicative function,Pattern recognition,Artificial intelligence,Image denoising,Invariant (mathematics),Logarithm,Contourlet,Mathematics
Journal
Volume
Issue
ISSN
73
10-12
Neurocomputing
Citations 
PageRank 
References 
17
0.69
28
Authors
6
Name
Order
Citations
PageRank
Yong Cheng1694.58
Yingkun Hou21498.66
Chunxia Zhao326419.32
Zuoyong Li434827.55
Yong Hu519738.46
Cailing Wang6202.08