Jiali Cui, Yunhong Wang, Junzhou Huang, T. Tan, Zhenan Sun
{"title":"An iris image synthesis method based on PCA and super-resolution","authors":"Jiali Cui, Yunhong Wang, Junzhou Huang, T. Tan, Zhenan Sun","doi":"10.1109/ICPR.2004.1333804","DOIUrl":null,"url":null,"abstract":"It is very important for the performance evaluation of iris recognition algorithms to construct very large iris databases. However, limited by the real conditions, there are no very large common iris databases now. In this paper, an iris image synthesis method based on principal component analysis (PCA) and super-resolution is proposed. The iris recognition algorithm based on PCA is first introduced and then, iris image synthesis method is presented. The synthesis method first constructs coarse iris images with the given coefficients. Then, synthesized iris images are enhanced using super-resolution. Through controlling the coefficients, we can create many iris images with specified classes. Extensive experiments show that the synthesized iris images have satisfactory cluster and the synthesized iris databases can be very large.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"135","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2004.1333804","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 135
Abstract
It is very important for the performance evaluation of iris recognition algorithms to construct very large iris databases. However, limited by the real conditions, there are no very large common iris databases now. In this paper, an iris image synthesis method based on principal component analysis (PCA) and super-resolution is proposed. The iris recognition algorithm based on PCA is first introduced and then, iris image synthesis method is presented. The synthesis method first constructs coarse iris images with the given coefficients. Then, synthesized iris images are enhanced using super-resolution. Through controlling the coefficients, we can create many iris images with specified classes. Extensive experiments show that the synthesized iris images have satisfactory cluster and the synthesized iris databases can be very large.