关键词: 人脸识别, 非采样Shearlet变换, 中心对称局部方向模式, 最近邻分类器

Abstract: To overcome the limitations of traditional face recognition methods under variations in position, illumination and expression, a novel method of face recognition based on Nonsubsampled Shearlet Transform（NSST） and Center-Symmetric Local Directional Pattern（CSLDP） is proposed. A face image is decomposed with NSST and CSLDP operator is utilized to get CSLDP feature maps from sub-images. CSLDP feature maps are divided into several blocks and the concatenated histogram calculated over each block is used as the face feature. Nearest neighbor classifier is used to classify the faces. Experimental results on ORL, YALE CAS-PEAL-R1 face databases demonstrate that the proposed descriptor is simple and effective, and also robust to variations of posture, illumination and face expression.

Key words: face recognition, Nonsubsampled Shearlet Transform（NSST）, Center-Symmetric Local Directional Pattern（CSLDP）, nearest neighbor classifier