{"title":"基于模糊支持向量机的虹膜识别方法","authors":"Hongying Gu, Zhiwen Gao, Cheng Yang","doi":"10.1109/ICMLA.2011.169","DOIUrl":null,"url":null,"abstract":"An iris recognition system named IrisPassport is presented in this paper. Standard Deviation is used to localize the irises from iris images. After localization, IrisPassport uses Steerable Pyramid and Variant Fractal Dimension as features with orientation information. Aiming to build a robust solution for non-cooperative iris images, we adopt fuzzy support vector machine (FSVM) because we consider different samples contributes to classification differently and a member function can be used when unclassifiable regions appear. Experimental data demonstrates the potential of our new approach, and shows that it performs favorably when compared with the former algorithms.","PeriodicalId":439926,"journal":{"name":"2011 10th International Conference on Machine Learning and Applications and Workshops","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Iris Recognition Approach based on Fuzzy Support Vector Machine\",\"authors\":\"Hongying Gu, Zhiwen Gao, Cheng Yang\",\"doi\":\"10.1109/ICMLA.2011.169\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An iris recognition system named IrisPassport is presented in this paper. Standard Deviation is used to localize the irises from iris images. After localization, IrisPassport uses Steerable Pyramid and Variant Fractal Dimension as features with orientation information. Aiming to build a robust solution for non-cooperative iris images, we adopt fuzzy support vector machine (FSVM) because we consider different samples contributes to classification differently and a member function can be used when unclassifiable regions appear. Experimental data demonstrates the potential of our new approach, and shows that it performs favorably when compared with the former algorithms.\",\"PeriodicalId\":439926,\"journal\":{\"name\":\"2011 10th International Conference on Machine Learning and Applications and Workshops\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 10th International Conference on Machine Learning and Applications and Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLA.2011.169\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 10th International Conference on Machine Learning and Applications and Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLA.2011.169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Iris Recognition Approach based on Fuzzy Support Vector Machine
An iris recognition system named IrisPassport is presented in this paper. Standard Deviation is used to localize the irises from iris images. After localization, IrisPassport uses Steerable Pyramid and Variant Fractal Dimension as features with orientation information. Aiming to build a robust solution for non-cooperative iris images, we adopt fuzzy support vector machine (FSVM) because we consider different samples contributes to classification differently and a member function can be used when unclassifiable regions appear. Experimental data demonstrates the potential of our new approach, and shows that it performs favorably when compared with the former algorithms.