Face Recognition Method Based on Support Vector Machine
Zhen Tao Yu · Jisuanji fangzhen · 2011
Face recognition in the field of pattern recognition is an important research topic,and it includes two key steps:the feature extraction and classifier design.In order to solve the adverse effects of illumination conditions on the face recognition,the paper proposed a face recognition algorithm(MSR-SVM) based on multi-scale Retinex(MSR) and support vector machine(SVM).Firstly,MSR-SVM adopted MSR to preprocess face image,and eliminated the harmful effects of light conditions.Then the PCA extracted facial image features,and finally face image was classified by classification algorithm SVM.Yale face library was used to test MSR-SVM algorithm.Simulation experiment results show that the MSR-SVM can eliminate the influences of illumination condition to face recognition,speed up the face recognition rate and improve the face recognition accuracy.