• DocumentCode
    2930829
  • Title

    Application of evolutionary algorithms for iris localization

  • Author

    Carneiro, M. ; Veiga, A. ; Castro, F.C. ; Flores, Edna Lucia ; Carrijo, G.A.

  • Author_Institution
    Dept. of Electr. Eng., Fed. Univ. of Uberlandia, Uberlandia, Brazil
  • fYear
    2009
  • fDate
    June 28 2009-July 3 2009
  • Firstpage
    506
  • Lastpage
    509
  • Abstract
    An iris recognition system requires efficient image processing techniques in order to duly represent and interpret the iris structural characteristics of an individual. The first processing stage should be the identification of the iris region in an eye image. This work introduces the application of evolutionary algorithms to localize the iris region in an eye image. A method based on memetic algorithms was proposed and used to find the circles that represent the external iris border and the pupil border in an edge map. The efficiency of the memetic algorithm in solving the problem was compared to the application of the Wildes´ method, which uses the circular Hough transform, a well known algorithm employed to find circles in an edged image. To test the algorithms, images from a public database were used. The results show that the proposed application has an encouraging performance.
  • Keywords
    Hough transforms; edge detection; evolutionary computation; Wilde method; circular Hough transform; edged image; evolutionary algorithm; eye image processing technique; iris recognition system; iris structural characteristics; public database; pupil border; Biological cells; Biology computing; Evolution (biology); Evolutionary computation; Image databases; Image edge detection; Image processing; Image segmentation; Iris recognition; Pixel; Biometry; Evolutionary Algorithms; Iris Recognition; Iris Segmentation; Memetic Algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on
  • Conference_Location
    New York, NY
  • ISSN
    1945-7871
  • Print_ISBN
    978-1-4244-4290-4
  • Electronic_ISBN
    1945-7871
  • Type

    conf

  • DOI
    10.1109/ICME.2009.5202544
  • Filename
    5202544