关键词: 人脸识别, 梯度, 尺度块局部二值模式（LBP）, 特征提取, 直方图, 降维

Abstract: In order to solve the problem that POEM （Pattern of Oriented Edge Magnitudes） ignores the pixel among blocks, a new face recognition method based on scaled-block LBP of oriented edge magnitude is proposed. Firstly, the orientation and magnitude of a face are extracted by gradient operator. The magnitude is accumulated on the basis of orientation with the same quantitative value. Secondly, divided histograms are extracted from each accumulated magnitude encoded by the scaled-block LBP operator. All the histograms are cascaded as the final recognition feature. Finally, the dimensionality reduction method of WPCA is used to improve the effectiveness of the proposed algorithm. Experimental result shows that the proposed algorithm is more robust than other comparing algorithms and can achieve good recognition performance with short dimension after feature dimensionality reduction method used.

Key words: face recognition, gradient, scaled-block Local Binary Pattern（LBP）, feature extraction, histogram, dimensionality reduction