关键词: 人脸识别, 单样本, 单演信号, 中心对称, 幅值相位方向模式, 中心对称局部二值模式（CS-LBP）

Abstract: To overcome the limitation of traditional single sample face recognition, a new method of face recognition based on Monogenic features and CS-LBP（MCSLBP） is proposed. Center-Symmetric Local Binary Pattern（CS-LBP） is firstly adopted to encode the monogenic magnitude on the same scale. The monogenic phase is quantified into four regions while encoded in horizontal direction and vertical direction. Then these three parts are integrated into MCSLBP feature. Finally, MCSLBP feature map at different scales is divided into several blocks, and the concatenated histogram features calculated over all blocks are used for the feature descriptor of face recognition, and the recognition is performed by using the nearest neighbor classifier. Experimental results on CAS-PEAL and AR databases show that the MCSLBP algorithm is an outstanding method for single sample face recognition under different illumination conditions, different facial expression conditions and partial occlusion conditions.

Key words: face recognition, single sample, monogenic signal, center-symmetric, magnitude phase and orientation pattern, Center-Symmetric Local Binary Pattern（CS-LBP）