Paper
12 April 2007 Dissimilarity functions for behavior-based biometrics
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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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Roman V. Yampolskiy and Venu Govindaraju "Dissimilarity functions for behavior-based biometrics", Proc. SPIE 6539, Biometric Technology for Human Identification IV, 65390P (12 April 2007); https://doi.org/10.1117/12.719008
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CITATIONS
Cited by 9 scholarly publications.
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KEYWORDS
Biometrics

Mahalanobis distance

Behavioral biometrics

Detection and tracking algorithms

Computing systems

Computer security

Databases

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