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Feature Level Fusion of Face and Palmprint Biometrics

  • Dakshina Ranjan Kisku
  • Phalguni Gupta
  • Jamuna Kanta Sing
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6218)

Abstract

This paper presents a feature level fusion of face and palmprint biometrics. It uses the improved K-medoids clustering algorithm and isomorphic graph. The performance of the system has been verified by two distance metrics namely, K-NN and normalized correlation metrics. It uses two multibiometrics databases of face and palmprint images for testing. The experimental results reveal that the feature level fusion with the improved K-medoids partitioning algorithm exhibits robust performance and increases its performance with utmost level of accuracy.

Keywords

Biometrics Feature Level Fusion Face Palmprint Isomorphic Graph K-Medoids Partitioning Algorithm 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Dakshina Ranjan Kisku
    • 1
  • Phalguni Gupta
    • 2
  • Jamuna Kanta Sing
    • 3
  1. 1.Department of Computer Science and EngineeringDr. B. C. Roy Engineering CollegeDurgapurIndia
  2. 2.Department of Computer Science and EngineeringIndian Institute of Technology KanpurKanpurIndia
  3. 3.Department of Computer Science and EngineeringJadavpur UniversityKolkataIndia

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