关键词: 人脸识别, 光照变化, 局部敏感直方图, 特征融合

Abstract: In order to solve the problem that the face recognition is greatly affected by illumination variation, a new face recognition method based on combine Locality Sensitive Histograms（LSH） and Laplacian of Gaussian（LoG） feature is proposed. Firstly, the LSH illumination invariant feature and the LoG edge feature are extracted from the facial image. Then, the adaptive fusion weight is determined by calculating the standard deviation of each feature, and the two features are fused to compensate for the loss of details when singly use LSH feature, and constructs a more effective set of face feature samples. Finally, the Sparse Representation based Classification（SRC） is used to classify. Experiments on the PIE and AR face database show that the proposed method can deal with the illumination problem well and obtain higher recognition rate even in the case of less training samples.

Key words: face recognition, illumination variation, locality sensitive histograms, feature fusion