关键词: 人脸识别, Gabor特征, 自商图像, 光照不变特征, 图像增强

Abstract:

Varying illumination remains one of the major challenges for current face recognition systems. To deal with the illumination variation problem, an improved self quotient images algorithm based on Gabor features is proposed. Firstly, the modified weighted Gabor filter is used to extract the Gabor feature of the face image, then the illumination invariant characteristics of the image is obtained by using the self quotient images algorithm. The self quotient image is normalized by histogram truncation. Finally, the experiment is carried out on Extended Yale B and CMU PIE face library by the nearest neighbor classifier based on Pearson correlation coefficient. Compared with the traditional algorithm, experimental results show that the algorithm significantly improves the face recognition rate.

Key words: face recognition, Gabor feature, self quotient image, illumination invariant, image enhancement