Iris Recognition Using Kernel FDA and SVM

摘要：

A new iris recognition algorithm,based on kernel fisher discriminant analysis (KFDA) and support vector machine (SVM),is proposed in this paper.Firstly,KFDA was applied to the iris images in order to extract texture feature then the support vector machine is adopted to classify and match iris features.The method is tested on CASIA iris images database.The experimental results of iris recognition showed that the proposed algorithm was effective and exhibited high operational speed.It also has high recognition accuracy.Therefore,it could be used in actual identification system.

关键词： Fisher discriminant analysis Support vector machine Pattern matching Iris recognition

作者: Shu Wang Zhenguo Chen

作者单位: Department of Computer North China Institute of Science and Technology East Yanjiao,Beijing,China

会议类型: 国际会议

会议名称: 2010 4th International Conference on Intelligent Information Techonlogy Application(第四届智能信息技术应用国际学术研讨会 IITA 2010)

会议地点: 秦皇岛

会议语种:英文

页码: 332-335

在线出版日期: 2010-11-05（万方平台首次上网日期，不代表论文的发表时间）