关键词: 人脸识别, 局部二元模式, 主成分分析, 支持向量机

Abstract: This paper proposes a robust method for face recognition under uncontrolled lighting condition. The effects of illumination variation are reduced by Gamma correction, DoG（Difference of Gauss filtering） and contrast equalization. The original image is divided into several non-overlapping cells and their corresponding histograms of Local Binary Pattern（LBP） are generated according to the characteristics of the local binary patterns in face image. PCA（Principal Component Analysis） is used to reduce the dimension of feature vector.The classification is made by SVM（Support Vector Machine）. The experimental results show that the average precision of the proposed algorithm is up to 99.68%, which indicates the performance of the proposed algorithm is better than that of the existing methods.

Key words: face recognition, Local Binary Pattern（LBP）, Principal Component Analysis（PCA）, Support Vector Machine（SVM）