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A Multi-algorithmic Colour Iris Recognition System

Radu, Petru and Sirlantzis, Konstantinos and Howells, Gareth and Hoque, Sanaul and Deravi, Farzin (2013) A Multi-algorithmic Colour Iris Recognition System. In: Soft Computing Applications Proceedings of the 5th International Workshop Soft Computing Applications (SOFA). Advances in Intelligent Systems and Computing . Springer, Berlin, Germany, pp. 45-56. ISBN 978-3-642-33940-0. E-ISBN 978-3-642-33941-7. (doi:10.1007/978-3-642-33941-7_7) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:35588)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1007/978-3-642-33941-7_7

Abstract

The reported accuracies of iris recognition systems are generally higher on near infrared images than on colour RGB images. To increase a colour iris recognition system’s performance, a possible solution is a multialgorithmic approach with an appropriate fusion mechanism. In the present work, this approach is investigated by fusing three algorithms at the score level to enhance the performance of a colour iris recognition system. The contribution of this paper consists of proposing 2 novel feature extraction methods for colour iris images, one based on a 3-bit encoder of the 8 neighborhood and the other one based on gray level co-occurrence matrix. The third algorithm employed uses the classical Gabor filters and phase encoding for feature extraction. A weighted average is used as a matching score fusion. The efficiency of the proposed iris recognition system is demonstrated on UBIRISv1 dataset.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-642-33941-7_7
Uncontrolled keywords: Iris Image, Feature Extraction Method, Equal Error Rate, False Acceptance Rate, False Reject Rate
Subjects: T Technology
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.P3 Pattern recognition systems
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Konstantinos Sirlantzis
Date Deposited: 22 Oct 2013 14:34 UTC
Last Modified: 05 Nov 2024 10:19 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/35588 (The current URI for this page, for reference purposes)

University of Kent Author Information

Radu, Petru.

Creator's ORCID:
CReDIT Contributor Roles:

Sirlantzis, Konstantinos.

Creator's ORCID: https://orcid.org/0000-0002-0847-8880
CReDIT Contributor Roles:

Howells, Gareth.

Creator's ORCID: https://orcid.org/0000-0001-5590-0880
CReDIT Contributor Roles:

Hoque, Sanaul.

Creator's ORCID: https://orcid.org/0000-0001-8627-3429
CReDIT Contributor Roles:

Deravi, Farzin.

Creator's ORCID: https://orcid.org/0000-0003-0885-437X
CReDIT Contributor Roles:
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