关键词: 人脸识别, 特征提取, 局部Gabor滤波器组, 自适应, 线性判别分析

Abstract: Concerning the time-consuming and computational complexity in extracting face features of traditional Gabor filters, the face features were extracted by using three different local Gabor filters adaptively chosen by the Gabor images' energy from different directions, scales and overall situation. Firstly, the Gabor features of some images in the face database were extracted and analyzed, and the local Gabor filters were built by choosing the filters corresponding to the images with larger energy. And then, the Fisher features were extracted using Linear Discriminate Analysis (LDA) further. Finally, face recognition was realized using the nearest neighbor method. The experimental results based on ORL and YALE face database show that the proposed approach has better face recognition performance with less feature dimension and calculation time.

Key words: face recognition, feature extraction, local-Gabor filters, adaptive, Linear Discriminate Analysis (LDA)