• DocumentCode
    3647823
  • Title

    Model-based pupil and iris localization

  • Author

    Nitin K. Mahadeo;Andrew P. Papliński;Sid Ray

  • Author_Institution
    Clayton School of Information Technology, Monash University, Australia
  • fYear
    2012
  • fDate
    6/1/2012 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    The iris is the most accurate biometric to date and its localization is a vital step in any iris recognition system. Iris localization can be considered as the search for the demarcation points, or step change in intensity at its boundaries. A failed localization will lead to incorrect iris segmentation and eventually to poor recognition. In the first stage, we proceed with the elimination of reflection and the reduction of lighting variations in eye images. In the second stage of our proposed system, radii and locations of the pupil and iris are obtained by maximizing the convolution of the image with a toroidal 2-D filtering shape derived from the Petrou-Kittler 1-D filter. Such a novel approach delivers robust localization of the inner and outer iris boundaries. We tested our system on a large dataset of poor quality eye images with substantial occlusions, illumination and defocus and the proposed algorithm is found to be robust and accurate.
  • Keywords
    "Iris","Iris recognition","Lighting","Image edge detection","Convolution","Image segmentation","Shape"
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2012 International Joint Conference on
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-1488-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2012.6252562
  • Filename
    6252562