Radu, Petru, Sirlantzis, Konstantinos, Howells, Gareth, Hoque, Sanaul, Deravi, Farzin (2011) Information Fusion for Unconstrained Iris Recognition. International Journal of Hybrid Information Technology, 4 (4). pp. 1-12. ISSN 1738-9968. (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:28334)
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. |
Abstract
The majority of the iris recognition algorithms available in the literature were developed to operate on near infrared images. A desirable feature of iris recognition systems with reduced constraints such as potential operability on commonly available hardware is to work with images acquired under visible wavelength. Unlike in near infrared images, in colour iris images the pigment melanin present in the iris tissue causes the appearance of reflections, which are one of the major noise factors present in colour iris images. In this paper we present an iris recognition system which is able to cope with noisy colour iris images by employing score level fusion between different channels of the iris image. The robustness of the proposed approach is tested on three colour iris images datasets, ranging from images captured with professional cameras in both constrained environment and less cooperative scenario, and finally to iris images acquired with a mobile phone.
Item Type: | Article |
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Uncontrolled keywords: | Unconstrained iris recognition, visible spectrum iris images, information fusion |
Subjects: | T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Konstantinos Sirlantzis |
Date Deposited: | 02 Nov 2011 12:27 UTC |
Last Modified: | 05 Nov 2024 10:09 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/28334 (The current URI for this page, for reference purposes) |
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