A study of identical twins' palmprints for personal authentication

Adams Kong; Dapeng Zhang; Guangming Lu

A study of identical twins' palmprints for personal authentication

Adams Kong, Dapeng Zhang, Guangming Lu

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

10 Citations (Scopus)

Abstract

Biometric recognition based on human characteristics for personal identification has attracted great attention. The performance of biometric systems highly depends on the distinctive information in the biometrics. However, identical twins having the closest genetics-based relationship are expected to have maximum similarity between their biometrics. Classifying identical twins is a challenging problem for some automatic biometric systems. In this paper, we summarize the exiting experimental results about identical twins' biometrics including face, iris, fingerprint and voice. Then, we systemically examine identical twins' palmprints. The experimental results show that we can employ low-resolution palmprint images to distinguish identical twins.

Original language	English
Title of host publication	Advances in Biometrics - International Conference, ICB 2006, Proceedings
Pages	668-674
Number of pages	7
Publication status	Published - 15 Jun 2006
Event	International Conference on Biometrics, ICB 2006 - Hong Kong, Hong Kong Duration: 5 Jan 2006 → 7 Jan 2006

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

Conference

Conference	International Conference on Biometrics, ICB 2006
Country/Territory	Hong Kong
City	Hong Kong
Period	5/01/06 → 7/01/06

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Cite this

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title = "A study of identical twins' palmprints for personal authentication",

abstract = "Biometric recognition based on human characteristics for personal identification has attracted great attention. The performance of biometric systems highly depends on the distinctive information in the biometrics. However, identical twins having the closest genetics-based relationship are expected to have maximum similarity between their biometrics. Classifying identical twins is a challenging problem for some automatic biometric systems. In this paper, we summarize the exiting experimental results about identical twins' biometrics including face, iris, fingerprint and voice. Then, we systemically examine identical twins' palmprints. The experimental results show that we can employ low-resolution palmprint images to distinguish identical twins.",

author = "Adams Kong and Dapeng Zhang and Guangming Lu",

year = "2006",

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

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note = "International Conference on Biometrics, ICB 2006 ; Conference date: 05-01-2006 Through 07-01-2006",

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Kong, A, Zhang, D & Lu, G 2006, A study of identical twins' palmprints for personal authentication. 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. 668-674, International Conference on Biometrics, ICB 2006, Hong Kong, Hong Kong, 5/01/06.

A study of identical twins' palmprints for personal authentication. / Kong, Adams; Zhang, Dapeng; Lu, Guangming.
Advances in Biometrics - International Conference, ICB 2006, Proceedings. 2006. p. 668-674 (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 / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AB - Biometric recognition based on human characteristics for personal identification has attracted great attention. The performance of biometric systems highly depends on the distinctive information in the biometrics. However, identical twins having the closest genetics-based relationship are expected to have maximum similarity between their biometrics. Classifying identical twins is a challenging problem for some automatic biometric systems. In this paper, we summarize the exiting experimental results about identical twins' biometrics including face, iris, fingerprint and voice. Then, we systemically examine identical twins' palmprints. The experimental results show that we can employ low-resolution palmprint images to distinguish identical twins.

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A study of identical twins' palmprints for personal authentication

Abstract

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ASJC Scopus subject areas

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