• DocumentCode
    3543374
  • Title

    Novel Iris Segmentation Method

  • Author

    Guesmi, H. ; Trichili, Hanene ; Alimi, Adel M. ; Solaiman, Basel

  • Author_Institution
    REGIM: Res. Group on Intell. Machines, Nat. Eng. Sch. of Sfax, Sfax, Tunisia
  • fYear
    2012
  • fDate
    10-12 May 2012
  • Firstpage
    260
  • Lastpage
    265
  • Abstract
    Iris recognition is a proven, accurate means to identify people. Iris is a part of an eye image. To be possible the uses of this modality, it´s indispensable to be detected and segmented. In this paper, we present our both methods: eye image preprocessing by method of Bias-Corrected Fuzzy C-Mean (BCFCM) and iris segmentation based on the active contours “Snake”. The performance of iris recognition system highly depends on segmentation step. 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 method for segmenting the iris patterns. To prove the performance of our iris method segmentation, we have integrated it in an iris verification system. Experiments are performed using iris images obtained from CASIA V.1 database.
  • Keywords
    feature extraction; fuzzy set theory; image segmentation; iris recognition; CASIA V.1 database; active contours; bias-corrected fuzzy c-mean; effective feature extraction method; eye image preprocessing by method; iris patterns; iris recognition; iris verification system; novel iris segmentation method; snake; straightforward method; Eyelids; Image segmentation; Iris recognition; Reliability; BCFCM; Snake; iris recognition; iris segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Computing and Systems (ICMCS), 2012 International Conference on
  • Conference_Location
    Tangier
  • Print_ISBN
    978-1-4673-1518-0
  • Type

    conf

  • DOI
    10.1109/ICMCS.2012.6320292
  • Filename
    6320292