虹膜分割方法综述

S. Jayalakshmi, M. Sundaresan
{"title":"虹膜分割方法综述","authors":"S. Jayalakshmi, M. Sundaresan","doi":"10.1109/ICPRIME.2013.6496513","DOIUrl":null,"url":null,"abstract":"In this paper, we have studied various well known Iris Segmentation algorithms which are used for the purpose of Iris recognition. We have gone through many algorithms based on Fourier spectral density, Limbic boundary localization, Gradient-Based edge detection and linking, Dempster-Shafer theory, Pupil detection, Fourier spectral density which will help us for accurate and efficient iris segmentation. In this paper we made a comparison of the results obtained from the implementation of existing algorithms, which will produce better result for segmentation with improved accuracy rate using the CASIA, WVU and UBIRIS databases.","PeriodicalId":123210,"journal":{"name":"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering","volume":"49 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A survey on Iris Segmentation methods\",\"authors\":\"S. Jayalakshmi, M. Sundaresan\",\"doi\":\"10.1109/ICPRIME.2013.6496513\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we have studied various well known Iris Segmentation algorithms which are used for the purpose of Iris recognition. We have gone through many algorithms based on Fourier spectral density, Limbic boundary localization, Gradient-Based edge detection and linking, Dempster-Shafer theory, Pupil detection, Fourier spectral density which will help us for accurate and efficient iris segmentation. In this paper we made a comparison of the results obtained from the implementation of existing algorithms, which will produce better result for segmentation with improved accuracy rate using the CASIA, WVU and UBIRIS databases.\",\"PeriodicalId\":123210,\"journal\":{\"name\":\"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering\",\"volume\":\"49 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPRIME.2013.6496513\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPRIME.2013.6496513","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

在本文中,我们研究了各种著名的虹膜分割算法,用于虹膜识别的目的。我们介绍了基于傅立叶谱密度、边缘边界定位、基于梯度的边缘检测和连接、Dempster-Shafer理论、瞳孔检测、傅立叶谱密度等算法,这些算法将有助于我们准确高效地分割虹膜。在本文中,我们对现有算法实现的结果进行了比较,使用CASIA、WVU和UBIRIS数据库会产生更好的分割结果,准确率也会提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A survey on Iris Segmentation methods
In this paper, we have studied various well known Iris Segmentation algorithms which are used for the purpose of Iris recognition. We have gone through many algorithms based on Fourier spectral density, Limbic boundary localization, Gradient-Based edge detection and linking, Dempster-Shafer theory, Pupil detection, Fourier spectral density which will help us for accurate and efficient iris segmentation. In this paper we made a comparison of the results obtained from the implementation of existing algorithms, which will produce better result for segmentation with improved accuracy rate using the CASIA, WVU and UBIRIS databases.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信