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Dissimilarity functions for behavior-based biometrics

  • SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

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.

Original languageEnglish
Title of host publicationBiometric Technology for Human Identification IV
DOIs
StatePublished - 2007
EventBiometric Technology for Human Identification IV - Orlando, FL, United States
Duration: Apr 9 2007Apr 10 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6539
ISSN (Print)0277-786X

Conference

ConferenceBiometric Technology for Human Identification IV
Country/TerritoryUnited States
CityOrlando, FL
Period04/9/0704/10/07

Keywords

  • Biometrics
  • Dissimilarity functions
  • Matching algorithm
  • Strategy biometrie

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