A personal identification system using retinal vasculature in retinal fundus images |
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| Authors: | Cemal Köse Cevat İki˙baş |
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| Affiliation: | 1. School of Computer Science and Technology, Shandong University, Jinan 250101, PR China;2. College of Science and Technology, Shandong University of Traditional Chinese Medicine, Jinan 250355, PR China;3. Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA;1. Department of Mathematics, “La Rábida” High Technical School of Engineering, University of Huelva, Spain;2. Department of Electronic, Computer Science and Automatic Engineering, “La Rábida” High Technical School of Engineering, University of Huelva, Spain;1. Faculty of Computers and Information, Cairo University, Egypt;2. Faculty of Computers and Information, Beni-Suef University, Egypt;3. Faculty of Mathematics and Computer Science, Babes-Bolyai University, Romania;1. Institute of Computer Science, Foundation for Research and Technology – Hellas (FORTH), Heraklion, Greece;2. Computer Science Department, University of Crete, Heraklion, Greece;3. Department of Internal Medicine, Papageorgiou Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece;1. Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;2. Department of Computer Engineering, Kharazmi University, Tehran, Iran;3. Department of Remote Sensing, K.N.Toosi University of Technology, Tehran, Iran;1. College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China;2. Department of Electrical & Electronic Engineering, Eastern Mediterranean University, Gazimagusa, Mersin, Turkey;3. Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan |
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| Abstract: | ![]()
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. |
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