Ayoub Ezzaki, Nadia Idrissi, Francisco-Angel Moreno, L. Masmoudi
{"title":"基于轮廓变换和熵的虹膜识别算法","authors":"Ayoub Ezzaki, Nadia Idrissi, Francisco-Angel Moreno, L. Masmoudi","doi":"10.5565/rev/elcvia.1190","DOIUrl":null,"url":null,"abstract":"The iris is one of the most secure biometric information that is widely employed in authentication systems. In this paper we present a method for iris recognition based on the Contourlet Transform and Entropy which entails i) the detection and segmentation of the iris, ii) its normalization, iii) the application of the Contourlet Transform, iv) the generation of the iris descriptor, and v) the matching between the query iris and those in the database. The proposed method has been tested with images taken from the popular CASIA-V4 and UBIRIS.v1 datasets and compared against four other iris recognition algorithms. The results show a higher true positive rate with a reduced computation time.","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Algorithm for Iris recognition based on contourlet Transform and Entropy\",\"authors\":\"Ayoub Ezzaki, Nadia Idrissi, Francisco-Angel Moreno, L. Masmoudi\",\"doi\":\"10.5565/rev/elcvia.1190\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The iris is one of the most secure biometric information that is widely employed in authentication systems. In this paper we present a method for iris recognition based on the Contourlet Transform and Entropy which entails i) the detection and segmentation of the iris, ii) its normalization, iii) the application of the Contourlet Transform, iv) the generation of the iris descriptor, and v) the matching between the query iris and those in the database. The proposed method has been tested with images taken from the popular CASIA-V4 and UBIRIS.v1 datasets and compared against four other iris recognition algorithms. The results show a higher true positive rate with a reduced computation time.\",\"PeriodicalId\":38711,\"journal\":{\"name\":\"Electronic Letters on Computer Vision and Image Analysis\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic Letters on Computer Vision and Image Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5565/rev/elcvia.1190\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Letters on Computer Vision and Image Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5565/rev/elcvia.1190","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
Algorithm for Iris recognition based on contourlet Transform and Entropy
The iris is one of the most secure biometric information that is widely employed in authentication systems. In this paper we present a method for iris recognition based on the Contourlet Transform and Entropy which entails i) the detection and segmentation of the iris, ii) its normalization, iii) the application of the Contourlet Transform, iv) the generation of the iris descriptor, and v) the matching between the query iris and those in the database. The proposed method has been tested with images taken from the popular CASIA-V4 and UBIRIS.v1 datasets and compared against four other iris recognition algorithms. The results show a higher true positive rate with a reduced computation time.