光照变化条件下的人脸识别技术研究  

Research on face recognition under illumination variations

作　　者：袁琳[1] 陈暄[1] 龙丹[2] 

机构地区：[1]浙江工业职业技术学院,浙江绍兴312008 [2]浙江大学,杭州310058

出　　处：《计算机工程与应用》2014年第4期196-199,239,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.30900358/C100701)

摘　　要：为了提高光照变化条件下的人脸识别率,针对Retinex算法处理人脸光照图像时易产生"光晕"难题,提出了一种基于Mean-Shift滤波的Retinex算法,并应用于人脸识别中的光照预处理。对人脸图像进行非线性增强;利用Mean-Shift滤波代替高斯滤波对光照估计,解决传统Retinex算法中存在的"光晕"难题。采用Yale B人脸库对算法性能进行测试,结果表明,该算法能够很好地抑制"光晕"现象的发生,具有光照鲁棒性,提高了人脸的识别率。In order to improve the face recognition rate under illumination variations, this paper proposes an improved retinex algorithm which Gauss filter is replaced by mean-shift filter to solve“halo”phenomenon in traditional retinex algo-rithm for face illumination image. The face image is enhanced by nonlinear method, and then mean-shift filter is used to estimate the illumination instead of gauss filter to solve the traditional retinex algorithm’s“halo”phenomenon problem. The algorithm’s performance is test by Yale B face database, the results show that the proposed algorithm can restrain the“halo”phenomenon and has illumination robustness to improve the face recognition rate.

关 键 词：光照预处理 人脸识别 RETINEX算法 Mean-Shift滤波 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]