• DocumentCode
    2921117
  • Title

    Iris Recognition System Using Statistical Features for Biometric Identification

  • Author

    Kyaw, Khin Sint Sint

  • Author_Institution
    Dept. of Eng. Phys., Mandalay Technol. Univ. Mandalay, Mandalay
  • fYear
    2009
  • fDate
    20-22 Feb. 2009
  • Firstpage
    554
  • Lastpage
    556
  • Abstract
    Iris recognition is a proven, accurate means to identify people. In this paper, it includes the preprocessing system, segmentation, feature extraction and recognition. Especially it focuses on image segmentation and statistical feature extraction for iris recognition process. The performance of iris recognition system highly depends on segmentation. For instance, even an effective feature extraction method would not be able to obtain useful information from an iris image that is not segmented properly. This paper presents a straightforward approach for segmenting the iris patterns. The used method determines an automated global threshold and the pupil center. Experiments are performed using iris images obtained from CASIA database. (Institute of Automation, Chinese Academy of Sciences) and Matlab application for its easy and efficient tools in image manipulation.
  • Keywords
    biometrics (access control); feature extraction; image segmentation; statistical analysis; CASIA database; Matlab; biometric identification; feature extraction; image manipulation; image segmentation; iris recognition system; statistical features; Biometrics; Feature extraction; Fingerprint recognition; Image databases; Image processing; Image segmentation; Iris recognition; Physics computing; Psychology; Speech; edge detection; feature vector; iris recognition; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Computer Technology, 2009 International Conference on
  • Conference_Location
    Macau
  • Print_ISBN
    978-0-7695-3559-3
  • Type

    conf

  • DOI
    10.1109/ICECT.2009.129
  • Filename
    4796024