Specific texture analysis for iris recognition

Emine Krichen; Lorène Allano; Sonia Garcia-Salicetti; Bernadette Dorizzi

doi:10.1007/11527923_3

Specific texture analysis for iris recognition

Emine Krichen
, Lorène Allano
, Sonia Garcia-Salicetti
, Bernadette Dorizzi

CNRS SAMOVAR UMR 5157

Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs

Résumé

In this paper, we present a new method for iris recognition based on specific texture analysis. It relies on the use of Haar wavelet analysis to extract the texture of the iris tissue. The matching is done using a specific correlation based on local peaks detection. Experiments have been conducted on the CASIA database in verification mode and show an EER of 0.07%. Degraded version of the CASIA database results in an EER of 2.3%, which is lower than result obtained by the classical wavelet demodulation (WD) method in that database.

langue originale	Anglais
Pages (de - à)	23-30
Nombre de pages	8
journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3546
Les DOIs	https://doi.org/10.1007/11527923_3
état	Publié - 1 janv. 2005
Modification externe	Oui
Evénement	5th International Conference on Audio - and Video-Based Biometric Person Authentication, AVBPA 2005 - Hilton Rye Town, NY, États-Unis Durée: 20 juil. 2005 → 22 juil. 2005

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10.1007/11527923_3

Contient cette citation

@article{bdd243ff1c3343d093f3a178df559845,

title = "Specific texture analysis for iris recognition",

abstract = "In this paper, we present a new method for iris recognition based on specific texture analysis. It relies on the use of Haar wavelet analysis to extract the texture of the iris tissue. The matching is done using a specific correlation based on local peaks detection. Experiments have been conducted on the CASIA database in verification mode and show an EER of 0.07\%. Degraded version of the CASIA database results in an EER of 2.3\%, which is lower than result obtained by the classical wavelet demodulation (WD) method in that database.",

author = "Emine Krichen and Lor{\`e}ne Allano and Sonia Garcia-Salicetti and Bernadette Dorizzi",

year = "2005",

month = jan,

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doi = "10.1007/11527923\_3",

language = "English",

volume = "3546",

pages = "23--30",

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

issn = "0302-9743",

note = "5th International Conference on Audio - and Video-Based Biometric Person Authentication, AVBPA 2005 ; Conference date: 20-07-2005 Through 22-07-2005",

}

Specific texture analysis for iris recognition. / Krichen, Emine; Allano, Lorène; Garcia-Salicetti, Sonia et al.
Dans: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol 3546, 01.01.2005, p. 23-30.

Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs

TY - JOUR

T1 - Specific texture analysis for iris recognition

AU - Krichen, Emine

AU - Allano, Lorène

AU - Garcia-Salicetti, Sonia

AU - Dorizzi, Bernadette

PY - 2005/1/1

Y1 - 2005/1/1

N2 - In this paper, we present a new method for iris recognition based on specific texture analysis. It relies on the use of Haar wavelet analysis to extract the texture of the iris tissue. The matching is done using a specific correlation based on local peaks detection. Experiments have been conducted on the CASIA database in verification mode and show an EER of 0.07%. Degraded version of the CASIA database results in an EER of 2.3%, which is lower than result obtained by the classical wavelet demodulation (WD) method in that database.

AB - In this paper, we present a new method for iris recognition based on specific texture analysis. It relies on the use of Haar wavelet analysis to extract the texture of the iris tissue. The matching is done using a specific correlation based on local peaks detection. Experiments have been conducted on the CASIA database in verification mode and show an EER of 0.07%. Degraded version of the CASIA database results in an EER of 2.3%, which is lower than result obtained by the classical wavelet demodulation (WD) method in that database.

U2 - 10.1007/11527923_3

DO - 10.1007/11527923_3

M3 - Conference article

AN - SCOPUS:26444476404

SN - 0302-9743

VL - 3546

SP - 23

EP - 30

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

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

T2 - 5th International Conference on Audio - and Video-Based Biometric Person Authentication, AVBPA 2005

Y2 - 20 July 2005 through 22 July 2005

ER -

Specific texture analysis for iris recognition

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