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基于球面谐波基图像的任意光照下的人脸识别
引用本文:卿来云,山世光,陈熙霖,高文. 基于球面谐波基图像的任意光照下的人脸识别[J]. 计算机学报, 2006, 29(5): 760-768
作者姓名:卿来云  山世光  陈熙霖  高文
作者单位:中国科学院研究生院,北京,100039;中国科学院计算技术研究所,北京,100080;中国科学院研究生院,北京,100039;中国科学院计算技术研究所,北京,100080
基金项目:国家高技术研究发展计划(863计划);中国科学院"百人计划";新世纪优秀人才支持计划;银晨智能识别科技有限公司资助项目
摘    要:提出了一种基于球面谐波基图像的光照补偿算法,用以在任意光照条件下进行人脸识别.算法分两步进行:光照估计和光照补偿.基于人脸形状大致相同和每个人脸的反射率基本相等的假设,首先估计了输入人脸图像光照的9个低频谐波系数.根据光照估计的结果,提出了两种光照补偿方法:纹理图像和差图像.纹理图像为输入图像与其光照辐照图之商,与输入图像的光照条件无关.差图像为输入图像与平均人脸在相同光照下的图像之差,通过减去平均人脸在相同光照下的图像,减弱了光照的影响.在CMU-PIE人脸库和Yale B人脸库上的实验表明,通过光照补偿,不同光照下人脸图像识别率有了很大提高.

关 键 词:人脸识别  光照变化  谐波基图像  光照估计  光照补偿
收稿时间:2005-11-06
修稿时间:2005-11-062006-02-28

Face Recognition under Varying Lighting Based on the Harmonic Images
QING Lai-Yun,SHAN Shi-Guang,CHEN Xi-Lin,GAO Wen. Face Recognition under Varying Lighting Based on the Harmonic Images[J]. Chinese Journal of Computers, 2006, 29(5): 760-768
Authors:QING Lai-Yun  SHAN Shi-Guang  CHEN Xi-Lin  GAO Wen
Affiliation:1. Graduate School of Chinese Academy of Sciences, Beijing 100039;2.Instituteof Computing Technology, ChineseAcademy of Sciences, Beijing 100080
Abstract:The performances of the current face recognition systems suffer heavily from the variations in lighting. To deal with this problem, this paper presents an illumination normalization approach based on the harmonic images model. There are two steps in the algorithm, illumination estimation and illumination normalization. Benefiting from the observations that human faces share similar shape, and the albedos of the face surfaces are quasi-constant, the authors first estimate the nine coefficients of the low-frequency components of the illumination. Then the authors compensate the effect of the illumination by defining two canonical images, the texture image and the difference image. The texture image is defined as the ratio between the input image and its Jrradiance and it is illumination invariant. The difference image is defined as the difference between the input image and the image of the average face model under the same illumination. Therefore the effect of the illumination is weakened and the valuable information for recognition is still en- coded in the difference image. The experiments on the CMU-PIE face database and the Yale B face database have shown that the proposed method improve the performance of a face recognition system significantly when the probes are collected under varying lighting conditions.
Keywords:face recognition   varying lighting   harmonic images   illumination estimation   illumination normalization
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