基于相位一致性图像的模块化PCA人脸识别方法

Novel modular PCA method based on phase congruency images for face recognition

提出了一种新的基于相位一致性的模块化PCA的人脸识别方法。解决了人脸识别受光照影响的问题。首先得到人脸训练样本的相位一致性图像;然后将人脸相位一致性图像划分为更小的子模块,用PCA方法处理这些子模块图像。在姿势、光照以及表情变化的情况下同一个人的局部面部特征是不变的,因此用该方法来处理这些变化。给出了传统的模块化PCA方法与该方法在不同姿势、光照和表情变化条件下的对比实验结果。实验结果表明该方法的人脸识别率较传统模块化PCA方法有了较大提高。

A novel modular PCA algorithm for face recognition based on phase congruency was presented. The accuracy of the modular PCA method and the proposed method were evaluated under the conditions of varying expression, illumination and pose using standard face databases. The results indicate high improvement in the classification performance compared to the conventional modular PCA method.