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Proceedings Paper

Dissimilarity functions for behavior-based biometrics
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Paper Abstract

Quality of a biometric system is directly related to the performance of the dissimilarity measure function. Frequently a generalized dissimilarity measure function such as Mahalanobis distance is applied to the task of matching biometric feature vectors. However, often accuracy of a biometric system can be greatly improved by introducing a customized matching algorithm optimized for a particular biometric. In this paper we investigate two tailored similarity measure functions for behavioral biometric systems based on the expert knowledge of the data in the domain. We compare performance of proposed matching algorithms to that of other well known similarity distance functions and demonstrate superiority of one of the new algorithms with respect to the chosen domain.

Paper Details

Date Published: 12 April 2007
PDF: 8 pages
Proc. SPIE 6539, Biometric Technology for Human Identification IV, 65390P (12 April 2007); doi: 10.1117/12.719008
Show Author Affiliations
Roman V. Yampolskiy, Univ. at Buffalo (United States)
Venu Govindaraju, Univ. at Buffalo (United States)


Published in SPIE Proceedings Vol. 6539:
Biometric Technology for Human Identification IV
Salil Prabhakar; Arun A. Ross, Editor(s)

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