Earticle

초록

영어

Remarkable improvements in recognition can be achieved through multibiometric fusion. Among various fusion techniques, score level fusion is the most frequently used in multibiometric system. In this paper, we propose a novel fusion algorithm based on False Reject Rate (FRR) and False Accept Rate (FAR) using Support Vector Machine (SVM). It transfers scores into corresponding FRRs and FARs, thus avoiding calculating posteriori probability of a certain score, as well as be capable of illustrating distribution of matching scores. The proposed method takes full advantages of both capabilities of FRR and FAR to describe the order of score and classification of SVM. Experimental results show that the proposed method outperforms existing representative approaches and can effectively improve the performance of multibiometric system.

목차

Abstract
 1. Introduction
 2. Transform the Score to FRR and FAR
  2.1. FRR and FAR calculation based on training set
  2.2. FRR and FAR calculation based on testing set
  2.3. An example for computation of FRR and FAR
 3. SVM Fusion Based on FRR and FAR
 4. Experiment Results
  4.1 Comparison with different fusion strategies
  4.2. Comparison with SVM-based strategies
 5. Conclusion
 Acknowledgments
 References

키워드

저자

• Yong Li [ Department of Information Engineering, Engineering University of CAPF, Xi’an China ]
• Meimei Shi [ Department of Science, Engineering University of CAPF, Xi'an, China ]
• En Zhu [ School of Computer, National University of Defense Technology, Changsha, Hunan Province, China ]
• Jianping Yin [ School of Computer, National University of Defense Technology, Changsha, Hunan Province, China ]
• Jianmin Zhao [ Top Key Discipline of Computer Software and Theory in Zhejiang Provincial Colleges, Zhejiang Normal University, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605