A novel fingerprint matching algorithm using ridge curvature feature

Peng Li; Xin Yang; Qi Su; Yangyang Zhang; Jie Tian

doi:10.1007/978-3-642-01793-3_62

A novel fingerprint matching algorithm using ridge curvature feature

Peng Li
, Xin Yang
, Qi Su
, Yangyang Zhang
, Jie Tian^*

^*Corresponding author for this work

CAS - Institute of Automation

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

6 Scopus citations

Abstract

Fingerprint matching based on solely minutiae feature ignore the abundant ridge information in fingerprint images. We propose a novel fingerprint matching algorithm which integrates minutiae feature with ridge curvature map(RCM). The RCM is approximated by a polynomial model which is computed by Least Square(LS) method. In the matching stage, phase-only correlation matching method is employed to match two RCMs. Then sum fusion rule is selected to combine the minutiae matching score and the RCM matching score. Experiments conducted on FVC2002 and FVC2004 databases show that proposed algorithm can obtain more promising performance than solely minutiae- based algorithm and several other multi-feature fusion algorithms.

Original language	English
Title of host publication	Advances in Biometrics - Third International Conference, ICB 2009, Proceedings
Publisher	Springer Verlag
Pages	607-616
Number of pages	10
ISBN (Print)	3642017924, 9783642017926
DOIs	https://doi.org/10.1007/978-3-642-01793-3_62
State	Published - 2009
Externally published	Yes
Event	3rd IAPR/IEEE International Conference on Advances in Biometrics, ICB 2009 - Alghero, Italy Duration: 2 Jun 2009 → 5 Jun 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5558 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd IAPR/IEEE International Conference on Advances in Biometrics, ICB 2009
Country/Territory	Italy
City	Alghero
Period	2/06/09 → 5/06/09

Keywords

Fingerprint matching
Phase - Only correlation
Polynomial model
RCM
Sum rule

Access to Document

10.1007/978-3-642-01793-3_62

Cite this

Li, P., Yang, X., Su, Q., Zhang, Y., & Tian, J. (2009). A novel fingerprint matching algorithm using ridge curvature feature. In Advances in Biometrics - Third International Conference, ICB 2009, Proceedings (pp. 607-616). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5558 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-642-01793-3_62

@inproceedings{bffad2f2be3449fb8439f2d9d9c1fa95,

title = "A novel fingerprint matching algorithm using ridge curvature feature",

abstract = "Fingerprint matching based on solely minutiae feature ignore the abundant ridge information in fingerprint images. We propose a novel fingerprint matching algorithm which integrates minutiae feature with ridge curvature map(RCM). The RCM is approximated by a polynomial model which is computed by Least Square(LS) method. In the matching stage, phase-only correlation matching method is employed to match two RCMs. Then sum fusion rule is selected to combine the minutiae matching score and the RCM matching score. Experiments conducted on FVC2002 and FVC2004 databases show that proposed algorithm can obtain more promising performance than solely minutiae- based algorithm and several other multi-feature fusion algorithms.",

keywords = "Fingerprint matching, Phase - Only correlation, Polynomial model, RCM, Sum rule",

author = "Peng Li and Xin Yang and Qi Su and Yangyang Zhang and Jie Tian",

year = "2009",

doi = "10.1007/978-3-642-01793-3\_62",

language = "英语",

isbn = "3642017924",

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

publisher = "Springer Verlag",

pages = "607--616",

booktitle = "Advances in Biometrics - Third International Conference, ICB 2009, Proceedings",

address = "德国",

note = "3rd IAPR/IEEE International Conference on Advances in Biometrics, ICB 2009 ; Conference date: 02-06-2009 Through 05-06-2009",

}

Li, P, Yang, X, Su, Q, Zhang, Y & Tian, J 2009, A novel fingerprint matching algorithm using ridge curvature feature. in Advances in Biometrics - Third International Conference, ICB 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5558 LNCS, Springer Verlag, pp. 607-616, 3rd IAPR/IEEE International Conference on Advances in Biometrics, ICB 2009, Alghero, Italy, 2/06/09. https://doi.org/10.1007/978-3-642-01793-3_62

A novel fingerprint matching algorithm using ridge curvature feature. / Li, Peng; Yang, Xin; Su, Qi et al.
Advances in Biometrics - Third International Conference, ICB 2009, Proceedings. Springer Verlag, 2009. p. 607-616 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5558 LNCS).

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

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AU - Su, Qi

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N2 - Fingerprint matching based on solely minutiae feature ignore the abundant ridge information in fingerprint images. We propose a novel fingerprint matching algorithm which integrates minutiae feature with ridge curvature map(RCM). The RCM is approximated by a polynomial model which is computed by Least Square(LS) method. In the matching stage, phase-only correlation matching method is employed to match two RCMs. Then sum fusion rule is selected to combine the minutiae matching score and the RCM matching score. Experiments conducted on FVC2002 and FVC2004 databases show that proposed algorithm can obtain more promising performance than solely minutiae- based algorithm and several other multi-feature fusion algorithms.

AB - Fingerprint matching based on solely minutiae feature ignore the abundant ridge information in fingerprint images. We propose a novel fingerprint matching algorithm which integrates minutiae feature with ridge curvature map(RCM). The RCM is approximated by a polynomial model which is computed by Least Square(LS) method. In the matching stage, phase-only correlation matching method is employed to match two RCMs. Then sum fusion rule is selected to combine the minutiae matching score and the RCM matching score. Experiments conducted on FVC2002 and FVC2004 databases show that proposed algorithm can obtain more promising performance than solely minutiae- based algorithm and several other multi-feature fusion algorithms.

KW - Fingerprint matching

KW - Phase - Only correlation

KW - Polynomial model

KW - RCM

KW - Sum rule

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ER -

Li P, Yang X, Su Q, Zhang Y, Tian J. A novel fingerprint matching algorithm using ridge curvature feature. In Advances in Biometrics - Third International Conference, ICB 2009, Proceedings. Springer Verlag. 2009. p. 607-616. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-01793-3_62

A novel fingerprint matching algorithm using ridge curvature feature

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Keywords

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