• DocumentCode
    2502479
  • Title

    How to Measure Biometric Information?

  • Author

    Sutcu, Yagiz ; Sencar, Husrev T. ; Memon, Nasir

  • Author_Institution
    Comput. Sci. & Eng. Dept., Polytech. Inst. of NYU, Brooklyn, NY, USA
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    1469
  • Lastpage
    1472
  • Abstract
    Being able to measure the actual information content of biometrics is very important but also a challenging problem. Main difficulty here is not only related to the selected feature representation of the biometric data, but also related to the matching algorithm employed in biometric systems. In this paper, we propose a new measure for measuring biometric information using relative entropy between intra-user and inter-user distance distributions. As an example, we evaluated the proposed measure on a face image dataset.
  • Keywords
    feature extraction; fingerprint identification; image matching; iris recognition; statistical analysis; biometric information; feature representation; interuser distance distribution; intrauser distance distribution; matching algorithm; relative entropy; Artificial neural networks; Bioinformatics; Databases; Entropy; Estimation; Face; Principal component analysis; biometric information; relative entropy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.363
  • Filename
    5597172