On some performance indices for biometric identification system

Jay Bhatnagar, Ajay Kumar Pathak

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

This paper investigates a new approach to formulate performance indices of biometric system using information theoretic models. The performance indices proposed here (unlike conventionally used FAR, GAR, DET etc.) are scalable in estimating performance of large scale biometric system. This work proposes a framework for identification capacity of a biometric system, along with insights on number of cohort users, capacity enhancements from user specific statistics etc. While incorporating feature level information in a rate-distortion framework, we derive condition for optimal feature representation. Furthermore, employing entropy measures to distance (hamming) distribution of the encoded templates, this paper proposes an upper bound for false random correspondence probability. Our analysis concludes that capacity can be the performance index of a biometric system while individuality expressed in false random correspondence can be the performance index of the biometric trait and representation. This paper also derives these indices and quantifies them from system parameters.
Original languageEnglish
Title of host publicationAdvances in Biometrics - International Conference, ICB 2007, Proceedings
Pages1043-1056
Number of pages14
Publication statusPublished - 1 Dec 2007
Externally publishedYes
Event2007 International Conference on Advances in Biometrics, ICB 2007 - Seoul, Korea, Republic of
Duration: 27 Aug 200729 Aug 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4642 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2007 International Conference on Advances in Biometrics, ICB 2007
Country/TerritoryKorea, Republic of
CitySeoul
Period27/08/0729/08/07

Keywords

  • FRC (false random correspondence probability)
  • Identification capacity
  • Individuality
  • Joint source-channel coding

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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