A novel method for coarse iris classification

Li Yu; Kuanquan Wang; Dapeng Zhang

A novel method for coarse iris classification

Li Yu, Kuanquan Wang, Dapeng Zhang

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

8 Citations (Scopus)

Abstract

This paper proposes a novel method for the automatic coarse classification of iris images using a box-counting method to estimate the fractal dimensions of the iris. First, the iris image is segmented into sixteen blocks, eight belonging to an upper group and eight to a lower group. We then calculate the fractal dimension value of these image blocks and take the mean value of the fractal dimension as the upper and the lower group fractal dimensions. Finally all the iris images are classified into four categories in accordance with the upper and the lower group fractal dimensions. This classification method has been tested and evaluated on 872 iris cases and the accuracy is 94.61 %. When we allow for the border effect, the double threshold algorithm is 98.28% accurate.

Original language	English
Title of host publication	Advances in Biometrics - International Conference, ICB 2006, Proceedings
Pages	404-410
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 novel method for coarse iris classification",

abstract = "This paper proposes a novel method for the automatic coarse classification of iris images using a box-counting method to estimate the fractal dimensions of the iris. First, the iris image is segmented into sixteen blocks, eight belonging to an upper group and eight to a lower group. We then calculate the fractal dimension value of these image blocks and take the mean value of the fractal dimension as the upper and the lower group fractal dimensions. Finally all the iris images are classified into four categories in accordance with the upper and the lower group fractal dimensions. This classification method has been tested and evaluated on 872 iris cases and the accuracy is 94.61 %. When we allow for the border effect, the double threshold algorithm is 98.28% accurate.",

author = "Li Yu and Kuanquan Wang and Dapeng Zhang",

year = "2006",

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

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Yu, L, Wang, K & Zhang, D 2006, A novel method for coarse iris classification. 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. 404-410, International Conference on Biometrics, ICB 2006, Hong Kong, Hong Kong, 5/01/06.

A novel method for coarse iris classification. / Yu, Li; Wang, Kuanquan; Zhang, Dapeng.
Advances in Biometrics - International Conference, ICB 2006, Proceedings. 2006. p. 404-410 (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

TY - GEN

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AU - Zhang, Dapeng

PY - 2006/6/15

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N2 - This paper proposes a novel method for the automatic coarse classification of iris images using a box-counting method to estimate the fractal dimensions of the iris. First, the iris image is segmented into sixteen blocks, eight belonging to an upper group and eight to a lower group. We then calculate the fractal dimension value of these image blocks and take the mean value of the fractal dimension as the upper and the lower group fractal dimensions. Finally all the iris images are classified into four categories in accordance with the upper and the lower group fractal dimensions. This classification method has been tested and evaluated on 872 iris cases and the accuracy is 94.61 %. When we allow for the border effect, the double threshold algorithm is 98.28% accurate.

AB - This paper proposes a novel method for the automatic coarse classification of iris images using a box-counting method to estimate the fractal dimensions of the iris. First, the iris image is segmented into sixteen blocks, eight belonging to an upper group and eight to a lower group. We then calculate the fractal dimension value of these image blocks and take the mean value of the fractal dimension as the upper and the lower group fractal dimensions. Finally all the iris images are classified into four categories in accordance with the upper and the lower group fractal dimensions. This classification method has been tested and evaluated on 872 iris cases and the accuracy is 94.61 %. When we allow for the border effect, the double threshold algorithm is 98.28% accurate.

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M3 - Conference article published in proceeding or book

SN - 3540311114

SN - 9783540311119

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

SP - 404

EP - 410

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

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Y2 - 5 January 2006 through 7 January 2006

ER -

A novel method for coarse iris classification

Abstract

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Conference

ASJC Scopus subject areas

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