计算机工程与应用2017，Vol.53Issue(6)：150-155,6.DOI:10.3778/j.issn.1002-8331.1508-0184
融合单演特征和CS-LBP的单样本人脸识别
Face recognition based on monogenic features and CS-LBP
摘要
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.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)Key words
face recognition/single sample/monogenic signal/center-symmetric/magnitude phase and orientation pattern/Center-Symmetric Local Binary Pattern(CS-LBP)分类
信息技术与安全科学引用本文复制引用
杨恢先,贺迪龙,谭正华,刘凡,刘阳..融合单演特征和CS-LBP的单样本人脸识别[J].计算机工程与应用,2017,53(6):150-155,6.基金项目
湖南省自然科学基金(No.14JJ3077) （No.14JJ3077）
湖南省教育厅一般项目(No.13C917). （No.13C917）
