{"title":"基于相关和协方差矩阵的视网膜识别分析","authors":"S. Kakarwal, R. Deshmukh","doi":"10.1109/ICETET.2010.29","DOIUrl":null,"url":null,"abstract":"We present an automated technique for person recognition based on retina of the human eye. In this paper we compare the performance of retina recognition by calculating correlation and covariance matrix of the retinal images. 20 images are used for the purpose of training and testing. Experimental results on DRIVE database show that these two methods are significantly better","PeriodicalId":175615,"journal":{"name":"2010 3rd International Conference on Emerging Trends in Engineering and Technology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Analysis of Retina Recognition by Correlation and Covariance Matrix\",\"authors\":\"S. Kakarwal, R. Deshmukh\",\"doi\":\"10.1109/ICETET.2010.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present an automated technique for person recognition based on retina of the human eye. In this paper we compare the performance of retina recognition by calculating correlation and covariance matrix of the retinal images. 20 images are used for the purpose of training and testing. Experimental results on DRIVE database show that these two methods are significantly better\",\"PeriodicalId\":175615,\"journal\":{\"name\":\"2010 3rd International Conference on Emerging Trends in Engineering and Technology\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 3rd International Conference on Emerging Trends in Engineering and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICETET.2010.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 3rd International Conference on Emerging Trends in Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETET.2010.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Retina Recognition by Correlation and Covariance Matrix
We present an automated technique for person recognition based on retina of the human eye. In this paper we compare the performance of retina recognition by calculating correlation and covariance matrix of the retinal images. 20 images are used for the purpose of training and testing. Experimental results on DRIVE database show that these two methods are significantly better