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. Springer Berlin Heidelberg pp. 45-56. ISBN 978-3-642-33940-0. (doi:https://doi.org/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)

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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: Conference or workshop item (Paper)
Subjects: T Technology
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications) > TK7880 Applications of electronics (inc industrial & domestic) > TK7882.B56 Biometrics
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications) > TK7880 Applications of electronics (inc industrial & domestic) > TK7882.P3 Pattern Recognition
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Konstantinos Sirlantzis
Date Deposited: 22 Oct 2013 14:34 UTC
Last Modified: 13 Dec 2015 22:14 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/35588 (The current URI for this page, for reference purposes)
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