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Fusion of Face and Iris Features for Multimodal Biometrics

  • Ching-Han Chen
  • Chia Te Chu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)

Abstract

The recognition accuracy of a single biometric authentication system is often much reduced due to the environment, user mode and physiological defects. In this paper, we combine face and iris features for developing a multimode biometric approach, which is able to diminish the drawback of single biometric approach as well as to improve the performance of authentication system. We combine a face database ORL and iris database CASIA to construct a multimodal biometric experimental database with which we validate the proposed approach and evaluate the multimodal biometrics performance. The experimental results reveal the multimodal biometrics verification is much more reliable and precise than single biometric approach.

Keywords

Multimodal biometrics face iris wavelet probabilistic neural network 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ching-Han Chen
    • 1
  • Chia Te Chu
    • 1
  1. 1.Institute of Electrical EngineeringI-Shou UniversityKaohsiung CountyTaiwan, R.O.C.

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