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xphe5: 金币+5, ★★★★★最佳答案, 感谢应助 2015-03-02 14:22:28
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A personal identification system using retinal vasculature in retinal fundus images
作者:Kose, C (Kose, Cemal)[ 1 ] ; Ikibas, C (Ikibas, Cevat)[ 1 ]
EXPERT SYSTEMS WITH APPLICATIONS
卷: 38  期: 11  页: 13670-13681
DOI: 10.1016/j.eswa.2011.04.141
出版年: OCT 2011
查看期刊信息
摘要
The characteristics of human body such as fingerprint, face, hand palm and iris are measured, recorded and identified by performing comparison using biometric devices. Even though it has not seen widespread acceptance yet, retinal identification based on retinal vasculatures in retina provides the most secure and accurate authentication means among biometric systems. Using retinal images taken from individuals, retinal identification is employed in environments such as nuclear research centers and facilities, weapon factories, where extremely high security measures are needed. The superiority of this method stems from the fact that retina is unique to every human being and it would not be changed during human life. Adversely, other identification approaches such as fingerprint, face, palm and iris recognition, are all vulnerable in that those characteristics can be corrupted via plastic surgeries and other changes. In this study we propose an alternate personal identification system based on retinal vascular network in retinal images, which tolerates scale, rotation and translation in comparison. In order to accurately identify a person our new approach first segments vessel structure and then employ similarity measurement along with the tolerations. The developed system, tested on about four hundred images, presents over 95% of success which is quite promising. (C) 2011 Elsevier Ltd. All rights reserved.
关键词
作者关键词:Biometric identification; Retinal identification; Retinal image analysis; Vessel segmentation; Similarity measurement
KeyWords Plus:MACULAR DEGENERATION; BLOOD-VESSELS; SEGMENTATION; DIAGNOSIS
作者信息
通讯作者地址: Kose, C (通讯作者)
显示增强组织信息的名称        Karadeniz Tech Univ, Fac Engn, Dept Comp Engn, TR-61080 Trabzon, Turkey.
地址:
显示增强组织信息的名称        [ 1 ] Karadeniz Tech Univ, Fac Engn, Dept Comp Engn, TR-61080 Trabzon, Turkey
电子邮件地址:ckose@ktu.edu.tr; cikibas@ktu.edu.tr
出版商
PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
类别 / 分类
研究方向:Computer Science; Engineering; Operations Research & Management Science
Web of Science 类别:Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; Operations Research & Management Science
文献信息
文献类型:Article
语种:English
入藏号: WOS:000294084700019
ISSN: 0957-4174
其他信息
IDS 号: 809VL
Web of Science 核心合集中的 "引用的参考文献": 33
Web of Science 核心合集中的 "被引频次": 6
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