Face Recognition Based on Enhanced Gabor Feature and Direct Fractional-Step Linear Discriminant Analysis
ZOU Jian-Fa1, WANG Guo-Yin1, GONG Xun2
1.Institute of Computer Science and Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065 2.School of Information Science and Technology,Southwest Jiaotong University,Chengdu 610031
Abstract：Gabor features can effectively represent the local features of face image with different directions and scales. However, traditional Gabor features based algorithms neglect the global features of the original image. Enhanced Gabor features (EGF) is developed in this paper by combining Gabor features and information extracted from the original image. A face recognition method is further proposed based on EGF and direct fractional-step linear discriminant analysis algorithm (DF_LDA). Experiment results of simulation on Yale, ORL and Georgia face databases show that EGF can effectively improve the face recognition rate compared with the traditional Gabor features.
邹建法，王国胤，龚勋. 基于增强Gabor特征和直接分步线性判别分析的人脸识别[J]. 模式识别与人工智能, 2010, 23(4): 477-482.
ZOU Jian-Fa, WANG Guo-Yin, GONG Xun. Face Recognition Based on Enhanced Gabor Feature and Direct Fractional-Step Linear Discriminant Analysis. , 2010, 23(4): 477-482.
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2010, Vol. 23 
