摘要
Abstract
In order to solve poor stability of its recognition of the current face recognition system of check on work at-tendance in the face of facial expression ,glasses ,hair interference ,this paper designed face recognition system of check on work attendance based on LBP Classifier (local binary pattern Classifier with the EigenFaces (face) .First of all ,through the optimization of high-dimensional feature ,low dimensional characteristics is refined ,the face detection is designed based on LBP Classifier operator ,face region is identified .And then the feature data is extracted ,human-machine interactive input is combined for supervised learning ,design the face recognition is decigned based on EigenFaces operator .Finally ,the recogni-tion of face charcteristics is finished .Experimental data shows that compared with the current face recognition algorithm ,in the face of the large interference of the expressions ,glasses ,hair this algorithm has higher stability and recognition rate .关键词
人脸识别/局部二值模式分类器/特征脸/低维特征/监督式学习Key words
face recognition/local binary pattern classifier/feature face/low dimensional feature/supervised learning分类
信息技术与安全科学
