Earticle

초록

영어

Conventional multimodal biometric identification systems tend to have larger memory footprint, slower processing speeds and a higher implementation and operational cost. In this paper we propose a state of the art framework for multimodal biometric identification system which can be adapted for any type of biometrics to provide smaller memory footprint and faster implementation than the conventional multimodal biometrics systems. The proposed framework is verified by development of a fingerprint and iris based fusion system which utilizes a single Hamming Distance matcher. Extensive testing is performed on the system running in identification mode and the results show that the system not only provides higher accuracy than the individual unimodal system but also the results are comparable to the conventional system.

목차

Abstract
 1. Introduction
 2. Proposed framework
  2.1. Feature extractor
  2.2. Matcher
  2.3. Fusion algorithm
 3. Experimental System
 4. Experimental results and analysis
 5. Conclusions
 References

저자

• Asim Baig [ Institute of Electronics, Communications and Information Technology (ECIT) Queen’s University ]
• Ahmed Bouridane [ School of Computing, Engineering and Information Sciences Northumbria University ]
• Fatih Kurugollu [ Institute of Electronics, Communications and Information Technology (ECIT) Queen’s University ]
• Gang Qu [ Electrical and Computer Engineering Department and Institute for Advanced Computer Studies. University of Maryland, College Park, Maryland, USA ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605