融合局部gabor相位特征和全局本征脸的人脸识别算法  

Face Recognition Based on Fusion of Local Gabor Phase Characteristic and Global Intrinsicfaces

作　　者：江艳霞[1] 王娟[1] 唐彩虹[1] 

机构地区：[1]上海理工大学光电信息与计算机工程学院自动化系,上海200093

出　　处：《小型微型计算机系统》2012年第9期2091-2095,共5页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(60874002)资助;上海市优秀青年教师基金项目(slg09008)资助;上海理工大学光电学院教师创新基金项目(GDCX-Y1110)资助

摘　　要：提出一种融合局部gabor相位特征和全局本征脸特征进行人脸识别的方法.该方法采用多个分类器的集成,首先利用gabor滤波良好的空间位置与方向选择特性,用gabor滤波器对图像进行滤波,采用局部XOR算子提取滤波图像的局部gabor相位特征,通过Fisher判别式对每个频率和方向下的相位特征进行降维,融合各个频率和方向下的分类概率,得出局部特征分类信息;然后利用本征判别式方法,得出人脸图像的全局分类信息;最后融合局部和全局分类信息进行识别.通过在三个人脸库中的实验结果显示,本文提出的方法具有很好的识别性能.A new face recognition method, which is based on fusion of local gabor phase characteristic and global intrinsicfaces is de- veloped in this paper. There are three steps in our proposed method. Firstly, According to the good spatial position and orientation of gabor filter, a gabor filter is applied to filter face images. Local gabor phase characteristics are extracted and fisher linear discriminant analysis is used to project these charactersitics of each spatial position and orientation into low dimensional space. Local classifying scores are developed by fusion of scores in all the spatial and orientations. Secondly, Intrinsic Discriminant Analysis （ IDA ） which tries to best classify different face images by maximizing the individuality difference, while minimizing the intrapersonal difference is applied to get the global classifying scores. Finally, the local scores and global scores are fused to get the classifying result. Experi- mental results on three dataset show that our method can have good recognition performance.

关 键 词：本征判别式分析 gabor相位特征 fisher线性判别式 人脸识别 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]