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Evaluating iris segmentation for scenario optimisation

Erbilek, Meryem and Fairhurst, Michael (2011) Evaluating iris segmentation for scenario optimisation. In: 4th International Conference on Imaging for Crime Detection and Prevention 2011 (ICDP 2011). IET, pp. 1-6. ISBN 978-1-84919-565-2. (doi:10.1049/ic.2011.0098) (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/10.1049/ic.2011.0098

Abstract

Iris recognition is a biometric modality which offers the potential for high accuracy and, increasingly, for application in more diverse environments than hitherto. Poor segmentation is one of the most important factors likely to compromise iris recognition performance. Hence, research in the area of iris biometrics has often been focused on efforts to enhance the performance of iris segmentation techniques, and this has led to considerable work on iris segmentation. This paper presents a detailed investigation, evaluation and comparison of several segmentation approaches (including a new algorithm proposed by the authors) proposed in the literature based on their accuracy and processing speed. To be consistent with the research of others, for all quantitative experiments, algorithms have been evaluated on two iris databases, namely CASIA V1.0 and a subset of the BioSecure database

Item Type: Book section
DOI/Identification number: 10.1049/ic.2011.0098
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Tina Thompson
Date Deposited: 30 Oct 2013 16:25 UTC
Last Modified: 10 Oct 2019 10:36 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/35842 (The current URI for this page, for reference purposes)
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