关键词: 人脸识别, 单样本, 拉普拉斯滤波, 中心对称局部二值模式, 最近邻分类器

Abstract: To overcome the limitations of traditional face recognition methods for single sample, a novel method of face recognition based on Laplace Filter and Center-symmetric Local Binary Pattern（LFCLBP） is proposed. Firstly, original face images are filtered by Laplace filter. Secondly, gradient magnitude maps and phase maps of a face image are calculated. A operator named Center-Symmetric Local Binary Pattern（CS-LBP） is proposed to encode the gradient magnitude, and gradient phase is quantized into sixteen regions, then the proposed LFCLBP is the combination of the binary codes of phase and CS-LBP of magnitude. Finally, LFCLBP feature maps are divided into several blocks, and the concatenated histogram calculates over all blocks are utilized as the feature descriptor of face recognition. The recognition is performed by using the nearest neighbor classifier. Experimental results on YALE and AR face databases validate that the LFCLBP 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, Laplace filter, Center-Symmetric Local Binary Pattern（CS-LBP）, nearest neighbor classifier