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Balancing Performance Factors in Multisource Biometric Processing Platforms

Fairhurst, Michael, da Costa-Abreu, Marjory (2009) Balancing Performance Factors in Multisource Biometric Processing Platforms. IET Signal Processing, 3 (4). pp. 342-351. ISSN 1751-9675. E-ISSN 1751-9683. (doi:10.1049/iet-spr.2008.0140) (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:24268)

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. 10.1049/iet-spr.2008.0140

Abstract

It is generally recognised that no one biometric data source or processing platform is universally appropriate for optimising performance across all problem domains. Multibiometric processors, which combine identity information obtained from more than one biometric source are commonly promoted as optimal structures for maximising performance, and much research has been carried out to investigate appropriate strategies for combining the available information. However, the techniques of multiclassifier pattern recognition also offer opportunities to improve the performance of systems operating within a unimodal environment, yet such solutions have been less extensively investigated n the specific case of biometric applications. This study presents an empirical study of the relations between these two different approaches to enhancing the performance indicators delivered by biometric systems. In particular, we are interested to increase our understanding of the relative mertis of, on the one hand, multiclassifier/single modality systems and, on the other, full multibiometric configurations. We focus our study on three modalities, the fingerprint and hand geometry (two physiological biometrics) and the handwritten signature (a behavioural biometric).

Item Type: Article
DOI/Identification number: 10.1049/iet-spr.2008.0140
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: J. Harries
Date Deposited: 15 Apr 2010 11:11 UTC
Last Modified: 16 Nov 2021 10:02 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/24268 (The current URI for this page, for reference purposes)

University of Kent Author Information

Fairhurst, Michael.

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da Costa-Abreu, Marjory.

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