Journal of the Korea Institute of Information Security & Cryptology (정보보호학회논문지)

Korea Institute of Information Security and Cryptology (한국정보보호학회)
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Performance Evaluation of Various Normalization Methods and Score-level Fusion Algorithms for Multiple-Biometric System

다중 생체 인식 시스템을 위한 정규화함수와 결합알고리즘의 성능 평가

  • Woo Na-Young (Biometric Engineering Research Center Graduate School of Information Technology & Telecommunication, Inha University) ;
  • Kim Hak-Il (Biometric Engineering Research Center Graduate School of Information Technology & Telecommunication, Inha University)
  • 우나영 (생체인식연구센터 인하대학교 정보통신대학원) ;
  • 김학일 (생체인식연구센터 인하대학교 정보통신대학원)
  • Published : 2006.06.01
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Abstract

The purpose of this paper is evaluation of various normalization methods and fusion algorithms in addition to pattern classification algorithms for multi-biometric systems. Experiments are performed using various normalization functions, fusion algorithms and pattern classification algorithms based on Biometric Scores Set-Releasel(BSSR1) provided by NIST. The performance results are presented by Half Total Error Rate (WTER). This study gives base data for the study on performance enhancement of multiple-biometric system by showing performance results using single database and metrics.

본 논문의 목적은 다중 생체 인식을 위하여 사용되는 다양한 정규화함수와 결합 및 패턴 분류 알고리즘들의 성능을 비교 평가하는 것이다. 이를 위하여 NIST에서 제공하는 유사도 집합인 BSSR(Biometric from Set-Releasel) 데이터베이스와 다양한 정규화함수, 결합 및 패턴 분류 알고리즘을 이용하여 실험을 수행하였으며, HTER(Half Total Error Rate)을 이용한 평가 결과를 제시하고 있다. 본 연구는 단일 데이터베이스와 평가 항목을 이용한 평가 결과를 제시함으로써 다중 생체 인식시스템의 성능 개선 연구를 위한 토대가 될 수 있다.

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