{"title":"基于单特征向量的虹膜识别","authors":"A. Basit, M. Javed, M. A. Anjum","doi":"10.1109/ICICT.2005.1598567","DOIUrl":null,"url":null,"abstract":"In this paper, an efficient method for personal identification based on the pattern of human iris is proposed. The system initially detects boundaries of iris, and then unwraps it into rectangular strip. A single vector is obtained corresponding to maximum eigen value and it is used as distinct feature of the iris. In the next step training is done and recognition decision is carried out by comparing the Euclidean distances with other feature vectors which determine whether two irises are similar or not. The results show that the success rate of the proposed method is 95.91%.","PeriodicalId":276741,"journal":{"name":"2005 International Conference on Information and Communication Technologies","volume":"93 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Iris Recognition Using Single Feature Vector\",\"authors\":\"A. Basit, M. Javed, M. A. Anjum\",\"doi\":\"10.1109/ICICT.2005.1598567\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an efficient method for personal identification based on the pattern of human iris is proposed. The system initially detects boundaries of iris, and then unwraps it into rectangular strip. A single vector is obtained corresponding to maximum eigen value and it is used as distinct feature of the iris. In the next step training is done and recognition decision is carried out by comparing the Euclidean distances with other feature vectors which determine whether two irises are similar or not. The results show that the success rate of the proposed method is 95.91%.\",\"PeriodicalId\":276741,\"journal\":{\"name\":\"2005 International Conference on Information and Communication Technologies\",\"volume\":\"93 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 International Conference on Information and Communication Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICT.2005.1598567\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 International Conference on Information and Communication Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICT.2005.1598567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, an efficient method for personal identification based on the pattern of human iris is proposed. The system initially detects boundaries of iris, and then unwraps it into rectangular strip. A single vector is obtained corresponding to maximum eigen value and it is used as distinct feature of the iris. In the next step training is done and recognition decision is carried out by comparing the Euclidean distances with other feature vectors which determine whether two irises are similar or not. The results show that the success rate of the proposed method is 95.91%.
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