• DocumentCode
    1864325
  • Title

    Iris Recognition Using Vector Quantization

  • Author

    Kekre, H.B. ; Sarode, T.K. ; Bharadi, V.A. ; Agrawal, A.A. ; Arora, R.J. ; Nair, M.C.

  • Author_Institution
    NMIMS Univ., Mumbai, India
  • fYear
    2010
  • fDate
    9-10 Feb. 2010
  • Firstpage
    58
  • Lastpage
    62
  • Abstract
    In today´s world, where terrorist attacks are on the rise, employment of infallible security systems is a must. Iris recognition enjoys universality, high degree of uniqueness and moderate user co-operation. This makes Iris recognition systems unavoidable in emerging security & authentication mechanisms. We propose an iris recognition system based on vector quantization. The proposed system does not need any pre-processing and segmentation of the iris. We have tested LBG, Kekre´s Proportionate Error Algorithm (KPE) & Kekre´s Fast Codebook Generation Algorithm (KFCG) for the clustering purpose. From the results it is observed that KFCG requires 99.79% less computations as that of LBG and KPE. Further the KFCG method gives best performance with the accuracy of 89.10% outperforming LBG that gives accuracy around 81.25%. Performance of individual methods is evaluated and presented in this paper.
  • Keywords
    authorisation; iris recognition; security; terrorism; vector quantisation; KFCG; KPE; Kekre fast codebook generation algorithm; Kekre proportionate error algorithm; LBG; authentication mechanisms; emerging security; infallible security systems; iris recognition; terrorist attacks; vector quantization; Biometrics; Clustering algorithms; Feature extraction; Image edge detection; Image recognition; Iris recognition; Security; Signal processing; Terrorism; Vector quantization; Biometrics; Iris recognition; KFCG; KPE; LBG; Vector Quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Acquisition and Processing, 2010. ICSAP '10. International Conference on
  • Conference_Location
    Bangalore
  • Print_ISBN
    978-1-4244-5724-3
  • Electronic_ISBN
    978-1-4244-5725-0
  • Type

    conf

  • DOI
    10.1109/ICSAP.2010.45
  • Filename
    5432650