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Advances in Multimedia
Volume 2017, Article ID 1356385, 11 pages
https://doi.org/10.1155/2017/1356385
Research Article

Efficient Gabor Phase Based Illumination Invariant for Face Recognition

1Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing 210044, China
2School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China

Correspondence should be addressed to Chunnian Fan; moc.361@tsiungniquuy

Received 13 June 2017; Revised 6 September 2017; Accepted 8 November 2017; Published 27 November 2017

Academic Editor: Haoran Xie

Copyright © 2017 Chunnian Fan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.