{"title":"基于b样条和小波的虹膜识别技术","authors":"S. Emerich, A. Discant, E. Lupu, S. Demea","doi":"10.1109/ISSCS.2007.4292748","DOIUrl":null,"url":null,"abstract":"Over recent years, applications of wavelet analysis are widespread and cover many fields of scientific research including biomedical science. We propose an iris classification method based on wavelet techniques. The fundamental theory for iris identification rests on the premise that every iris is individually characteristic enough to distinguish it from others through image analysis. In our study we are using different wavelet and scaling functions, including the recent discovered family of fractional B-splines. To perform the classification task we use the Weka system.","PeriodicalId":225101,"journal":{"name":"2007 International Symposium on Signals, Circuits and Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"B-spline and Wavelet Based Techniques for Iris Recognition\",\"authors\":\"S. Emerich, A. Discant, E. Lupu, S. Demea\",\"doi\":\"10.1109/ISSCS.2007.4292748\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Over recent years, applications of wavelet analysis are widespread and cover many fields of scientific research including biomedical science. We propose an iris classification method based on wavelet techniques. The fundamental theory for iris identification rests on the premise that every iris is individually characteristic enough to distinguish it from others through image analysis. In our study we are using different wavelet and scaling functions, including the recent discovered family of fractional B-splines. To perform the classification task we use the Weka system.\",\"PeriodicalId\":225101,\"journal\":{\"name\":\"2007 International Symposium on Signals, Circuits and Systems\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Symposium on Signals, Circuits and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSCS.2007.4292748\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Symposium on Signals, Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCS.2007.4292748","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
B-spline and Wavelet Based Techniques for Iris Recognition
Over recent years, applications of wavelet analysis are widespread and cover many fields of scientific research including biomedical science. We propose an iris classification method based on wavelet techniques. The fundamental theory for iris identification rests on the premise that every iris is individually characteristic enough to distinguish it from others through image analysis. In our study we are using different wavelet and scaling functions, including the recent discovered family of fractional B-splines. To perform the classification task we use the Weka system.