关键词: Gabor特征, 人脸识别, 鲁棒性, 局部归一化, 熵权法

Abstract: For the big challenge difficulty of face recognition under the complex environments, a fusion method based on entropy weighted method and local Gabor features is proposed. Class entropy weighting vectors are calculated. Borda count matrix is calculated to remove low-value Gabor jet comparison matrix. Layered class entropy weighted Gabor feature is fused with LGBP and LGXP respectively so as to finish face recognition. Experimental results on FERET, AR, and FRGC 2.0 databases show that proposed method shows significant robustness to slight pose variations and errors of up to 3 pixels in eye detection. It has better recognition efficiency than several other recognition methods.

Key words: Gabor feature, face identification, robust, local normalization, entropy weighted method