Fairhurst, M.C. and Abreu, M.C.D. (2009) Balancing Performance Factors in Multisource Biometric Processing Platforms. IET Signal Processing, 3 (4). pp. 342-351. ISSN 1751-9675.
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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).
|Subjects:||T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications) > TK7880 Applications of electronics (inc industrial & domestic) > TK7882.B56 Biometrics|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Image and Information Engineering|
|Depositing User:||Jenny Harries|
|Date Deposited:||15 Apr 2010 11:11|
|Last Modified:||03 Oct 2012 15:45|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/24268 (The current URI for this page, for reference purposes)|
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