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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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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author Chunnian Fan
Shuiping Wang
Hao Zhang
author_facet Chunnian Fan
Shuiping Wang
Hao Zhang
author_sort Chunnian Fan
collection DOAJ
description 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.
format Article
id doaj-art-82d5cb47120a468bb6df8a58f35b19f0
institution OA Journals
issn 1687-5680
1687-5699
language English
publishDate 2017-01-01
publisher Wiley
record_format Article
series Advances in Multimedia
spelling doaj-art-82d5cb47120a468bb6df8a58f35b19f02025-08-20T02:08:46ZengWileyAdvances in Multimedia1687-56801687-56992017-01-01201710.1155/2017/13563851356385Efficient Gabor Phase Based Illumination Invariant for Face RecognitionChunnian Fan0Shuiping Wang1Hao Zhang2Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaJiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaThis 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.http://dx.doi.org/10.1155/2017/1356385
spellingShingle Chunnian Fan
Shuiping Wang
Hao Zhang
Efficient Gabor Phase Based Illumination Invariant for Face Recognition
Advances in Multimedia
title Efficient Gabor Phase Based Illumination Invariant for Face Recognition
title_full Efficient Gabor Phase Based Illumination Invariant for Face Recognition
title_fullStr Efficient Gabor Phase Based Illumination Invariant for Face Recognition
title_full_unstemmed Efficient Gabor Phase Based Illumination Invariant for Face Recognition
title_short Efficient Gabor Phase Based Illumination Invariant for Face Recognition
title_sort efficient gabor phase based illumination invariant for face recognition
url http://dx.doi.org/10.1155/2017/1356385
work_keys_str_mv AT chunnianfan efficientgaborphasebasedilluminationinvariantforfacerecognition
AT shuipingwang efficientgaborphasebasedilluminationinvariantforfacerecognition
AT haozhang efficientgaborphasebasedilluminationinvariantforfacerecognition