Fake iris detection by using purkinje image

Eui Chul Lee; Kang Ryoung Park; Jaihie Kim

Fake iris detection by using purkinje image

Eui Chul Lee, Kang Ryoung Park, Jaihie Kim

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

87 Citations (Scopus)

Abstract

Fake iris detection is to detect and defeat a fake (forgery) iris image input. To solve the problems of previous researches on fake iris detection, we propose the new method of detecting fake iris attack based on the Purkinje image. Especially, we calculated the theoretical positions and distances between the Purkinje images based on the human eye model and the performance of fake detection algorithm could be much enhanced by such information. Experimental results showed that the FAR (False Acceptance Rate for accepting fake iris as live one) was 0.33% and FRR(False Rejection Rate of rejecting live iris as fake one) was 0.33%.

Original language	English
Title of host publication	Advances in Biometrics - International Conference, ICB 2006, Proceedings
Pages	397-403
Number of pages	7
Publication status	Published - 2006
Event	International Conference on Biometrics, ICB 2006 - Hong Kong, China Duration: 2006 Jan 5 → 2006 Jan 7

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3832 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	International Conference on Biometrics, ICB 2006
Country	China
City	Hong Kong
Period	06/1/5 → 06/1/7

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

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@inproceedings{5b3846d20c62496f8a661228322fc069,

title = "Fake iris detection by using purkinje image",

abstract = "Fake iris detection is to detect and defeat a fake (forgery) iris image input. To solve the problems of previous researches on fake iris detection, we propose the new method of detecting fake iris attack based on the Purkinje image. Especially, we calculated the theoretical positions and distances between the Purkinje images based on the human eye model and the performance of fake detection algorithm could be much enhanced by such information. Experimental results showed that the FAR (False Acceptance Rate for accepting fake iris as live one) was 0.33% and FRR(False Rejection Rate of rejecting live iris as fake one) was 0.33%.",

author = "Lee, {Eui Chul} and Park, {Kang Ryoung} and Jaihie Kim",

year = "2006",

language = "English",

isbn = "3540311114",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "397--403",

booktitle = "Advances in Biometrics - International Conference, ICB 2006, Proceedings",

}

Lee, EC, Park, KR & Kim, J 2006, Fake iris detection by using purkinje image. in Advances in Biometrics - International Conference, ICB 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3832 LNCS, pp. 397-403, International Conference on Biometrics, ICB 2006, Hong Kong, China, 06/1/5.

Fake iris detection by using purkinje image. / Lee, Eui Chul; Park, Kang Ryoung; Kim, Jaihie.

Advances in Biometrics - International Conference, ICB 2006, Proceedings. 2006. p. 397-403 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3832 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

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AU - Lee, Eui Chul

AU - Park, Kang Ryoung

AU - Kim, Jaihie

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N2 - Fake iris detection is to detect and defeat a fake (forgery) iris image input. To solve the problems of previous researches on fake iris detection, we propose the new method of detecting fake iris attack based on the Purkinje image. Especially, we calculated the theoretical positions and distances between the Purkinje images based on the human eye model and the performance of fake detection algorithm could be much enhanced by such information. Experimental results showed that the FAR (False Acceptance Rate for accepting fake iris as live one) was 0.33% and FRR(False Rejection Rate of rejecting live iris as fake one) was 0.33%.

AB - Fake iris detection is to detect and defeat a fake (forgery) iris image input. To solve the problems of previous researches on fake iris detection, we propose the new method of detecting fake iris attack based on the Purkinje image. Especially, we calculated the theoretical positions and distances between the Purkinje images based on the human eye model and the performance of fake detection algorithm could be much enhanced by such information. Experimental results showed that the FAR (False Acceptance Rate for accepting fake iris as live one) was 0.33% and FRR(False Rejection Rate of rejecting live iris as fake one) was 0.33%.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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