• DocumentCode
    2160269
  • Title

    Biometric hash: A study on statistical quantization methods

  • Author

    Karabat, Cagatay ; Erdogan, Hakan

  • Author_Institution
    BILGEM, Ulusal Elektron. ve Kriptoloji Arastirma Enstitusu, TUBITAK, Gebze, Turkey
  • fYear
    2012
  • fDate
    18-20 April 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The binary quantization method which is used in random projection based biometric hashing systems reduces the authentication performance of these systems. In this paper, we propose new statistical quantization methods for biometric hashing systems. Our proposed quantization methods use Gaussian mixture model and Gaussian distributions to determine quantization threshold value. Therefore, we improve the authentication performance of the biometric hashing systems with our proposed quantization methods. We also provide experimental results of the proposed methods. The experiments are achieved on the AT&T face database, comprising 400 face images from 20 subjects.
  • Keywords
    authorisation; biometrics (access control); cryptography; face recognition; file organisation; quantisation (signal); AT&T face database; Gaussian distributions; Gaussian mixture; authentication performance; binary quantization; biometric hashing systems; face images; random projection; statistical quantization; Authentication; Biological system modeling; Databases; Face; Manganese; Privacy; Quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2012 20th
  • Conference_Location
    Mugla
  • Print_ISBN
    978-1-4673-0055-1
  • Electronic_ISBN
    978-1-4673-0054-4
  • Type

    conf

  • DOI
    10.1109/SIU.2012.6204595
  • Filename
    6204595