Efficient Gabor Phase Based Illumination Invariant for Face Recognition

This paper presents a novel Gabor phase based illumination invariant extraction method aiming at eliminating the effect of varying illumination on face recognition. Firstly, It normalizes varying illumination on face images, which can reduce the effect of varying illumination to some extent. Secondl...

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Bibliographic Details
Main Authors: Chunnian Fan, Shuiping Wang, Hao Zhang
Format: Article
Language:English
Published: Wiley 2017-01-01
Series:Advances in Multimedia
Online Access:http://dx.doi.org/10.1155/2017/1356385
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Summary:This paper presents a novel Gabor phase based illumination invariant extraction method aiming at eliminating the effect of varying illumination on face recognition. Firstly, It normalizes varying illumination on face images, which can reduce the effect of varying illumination to some extent. Secondly, a set of 2D real Gabor wavelet with different directions is used for image transformation, and multiple Gabor coefficients are combined into one whole in considering spectrum and phase. Lastly, the illumination invariant is obtained by extracting the phase feature from the combined coefficients. Experimental results on the Yale B and the CMU PIE face database show that our method obtained a significant improvement over other related methods for face recognition under large illumination variation condition.
ISSN:1687-5680
1687-5699