A Novel Method for Multibiometric Fusion Based on FAR and FRR

  • Yong Li
  • Jianping Yin
  • Jun Long
  • En Zhu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5861)


Based on the fusion of multiple biometric sources, Multibiometric systems can be expected to be more accurate due to the presence of multiple pieces of evidence. Multibiometric system design is a challenging problem because it is very difficult to choose the optimal fusion strategy. Score level fusion is the most commonly used approach in Multibiometric systems. The distribution of genuine and imposter scores are very important for score fusion of Multibiometric systems. FRR (False Reject Rate) and FAR (False Accept Rate) are two key parameters to cultivate the distribution of genuine and imposter scores. In this paper, we first present a model for Multibiometric fusion and then proposed a novel approach for score level fusion which is based on FAR and FRR. By this method, the match scores first are transformed into LL1s and then the sum rule is used to combine the LL1s of the scores. The experimental results show that the new fusion scheme is efficient for different Multibiometric systems.


biometrics Multibiometric score level fusion multi-modal FRR FAR 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Yong Li
    • 1
  • Jianping Yin
    • 1
  • Jun Long
    • 1
  • En Zhu
    • 1
  1. 1.School of ComputerNational University of Defense TechnologyChangshaChina

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