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Image Enhancement vs Feature Fusion in Colour Iris Recognition

Radu, Petru and Sirlantzis, Konstantinos and Howells, Gareth and Hoque, Sanaul and Deravi, Farzin (2012) Image Enhancement vs Feature Fusion in Colour Iris Recognition. In: 2012 Third International Conference on Emerging Security Technologies. IEEE, pp. 53-57. ISBN 978-1-4673-2448-9. E-ISBN 978-0-7695-4791-6. (doi:10.1109/EST.2012.33) (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)

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. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/EST.2012.33

Abstract

In iris recognition, most of the research was conducted on operation under near infrared illumination. For an iris recognition system to be deployed on common hardware devices, such as laptops or mobile phones, its ability of working with visible spectrum iris images is necessary. Two of the main possible approaches to cope with noisy images in a colour iris recognition system are either to apply image enhancement techniques or to extract multiple types of features and subsequently to employ an efficient fusion mechanism. The contribution of the present paper consists of comparing which of the two above mentioned approaches is best in both identification and verification scenarios of a colour iris recognition system. The efficiency of the two approaches is demonstrated on UBIRISv1 dataset

Item Type: Book section
DOI/Identification number: 10.1109/EST.2012.33
Uncontrolled keywords: iris recognition; feature extraction; image color analysis; image enhancement; accuracy; entropy; principal component analysis
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Konstantinos Sirlantzis
Date Deposited: 31 Oct 2013 14:08 UTC
Last Modified: 24 Sep 2019 12:49 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/35887 (The current URI for this page, for reference purposes)
Hoque, Sanaul: https://orcid.org/0000-0001-8627-3429
Deravi, Farzin: https://orcid.org/0000-0003-0885-437X
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