A NOVEL METHOD OF FACE RECOGNITION BASED ON THE FUSION OF CLASSIFIERS

摘要：

Rough neural network has the advantage of reducing training time and optimizing network topology architecture.According to such attribute, a novel face recognition method is presented based on multi-features using fusion of multiple rough neural network classifiers. First, three different feature domains are used for extracting features from input images,including IO (the interest operator), PCA (the principal component analysis) and FLD(the Fishers linear discriminant). Second, three independent rough neural network classifiers are used for recognition in three different feature domains respectively. Then a modified vote rule is used for decision-fusion of multiple face recognition classifiers.Experimental results show that the face recognition method proposed in this paper possesses good the classification accuracy and the reliable recognition rate.

关键词： Face recognition Rough set Rough neural network Feature domain Fusion of multiple classifiers

作者: MING LI ZHI-YUN LIU

作者单位: School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3837-3841

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）