基于特征的弹性图匹配人脸识别算法

Feature-Based Face Recognition by Elastic Graph Matching

提出一种基于特征的弹性图匹配人脸识别算法 (FEGM) .它包括两个步骤 ,首先利用 Gabor进行人脸特征(如眼、鼻子、嘴等 )的检测、定位 ,提取一组 Gabor小波系数矢量 ;然后在代价函数的约束下 ,对各个特征都执行弹性图匹配 ,并使总体代价函数尽可能的小 ,从而得到联合识别结果 .在 Yale人脸库上的实验表明 ,识别率确实得到提高 .

A feature based elastic graph matching algorithm (FEGM) on the basis of the Lades' elastic graph matching face recognition algorithm is proposed in this paper. It includes two steps. First, the face feature such as eye, nose, mouth are localized by Gabor transforms, and a group of feature vectors composed by Gabor coefficients is extracted. Then the FEGM algorithm is performed to make the total cost function as small as possible, recognition result on Yale face database shows that recognition rate has been improved substantially.