Fake iris detection by using purkinje image

Eui Chul Lee, Kang Ryoung Park, Jaihie Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

77 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 languageEnglish
Title of host publicationAdvances in Biometrics - International Conference, ICB 2006, Proceedings
Pages397-403
Number of pages7
Publication statusPublished - 2006 Jun 15
EventInternational Conference on Biometrics, ICB 2006 - Hong Kong, China
Duration: 2006 Jan 52006 Jan 7

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3832 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Biometrics, ICB 2006
CountryChina
CityHong Kong
Period06/1/506/1/7

Fingerprint

Iris
Rejection
Attack
Experimental Results
Research

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Lee, E. C., Park, K. R., & Kim, J. (2006). Fake iris detection by using purkinje image. In Advances in Biometrics - International Conference, ICB 2006, Proceedings (pp. 397-403). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3832 LNCS).
Lee, Eui Chul ; Park, Kang Ryoung ; Kim, Jaihie. / Fake iris detection by using purkinje image. Advances in Biometrics - International Conference, ICB 2006, Proceedings. 2006. pp. 397-403 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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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",
month = "6",
day = "15",
language = "English",
isbn = "3540311114",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
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booktitle = "Advances in Biometrics - International Conference, ICB 2006, Proceedings",

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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 proceedingConference contribution

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T1 - Fake iris detection by using purkinje image

AU - Lee, Eui Chul

AU - Park, Kang Ryoung

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PY - 2006/6/15

Y1 - 2006/6/15

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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M3 - Conference contribution

SN - 3540311114

SN - 9783540311119

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

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BT - Advances in Biometrics - International Conference, ICB 2006, Proceedings

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Lee EC, Park KR, Kim J. Fake iris detection by using purkinje image. In 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)).