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Fusion of Gaussian Mixture Densities for Face and Ear Biometrics Using Support Vector Machines

  • Dakshina Ranjan Kisku
  • Phalguni Gupta
  • Jamuna Kanta Sing
  • Mita Nasipuri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6485)

Abstract

This paper presents a multimodal biometric system for face and ear biometrics which convolves face and ear images with Gabor wavelet filters for extracting enhanced Gabor features from the corresponding images which are characterized by spatial frequency, spatial locality and orientation. Gaussian Mixture Model (GMM) is applied to the Gabor responses for measurements and Expectation Maximization algorithm is used to estimate density parameters in GMM. It produces two sets of feature sets which are fused using Support Vector Machines. Experiments on two different databases reveal its usefulness towards robust multimodal fusion.

Keywords

Multimodal biometrics Face Ear Gabor wavelet filter Gaussian Mixture Model Support Vector Machines 

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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
  • Mita Nasipuri
    • 3
  1. 1.Department of Computer Science and EngineeringAsansol Engineering CollegeAsansolIndia
  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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