• DocumentCode
    2759033
  • Title

    Iris Localization Scheme Based on Morphology and Gaussian Filtering

  • Author

    Gui, Feng ; Qiwei, Lin

  • Author_Institution
    Dept. of Electron. & Commun., HuaQiao Univ., Quanzhou
  • fYear
    2007
  • fDate
    16-18 Dec. 2007
  • Firstpage
    798
  • Lastpage
    803
  • Abstract
    One of the basic techniques in iris recognition system is iris localization. To find a fast, effective and exact iris localization algorithm is the key step of iris recognition. After analyzing the principle, strong points and short points of some common used iris localization methods, a morphological theory based iris localization algorithm was proposed in this paper. Based on the concept of all the object can be regarded as the subset in Euclidean space, and this subset can totally reflect the shape, volume, texture and grey value of the object, so we can apply the morphology operation to identify the feature in different eye area. The proposed iris localization algorithm is as follow: iris image preprocessing at first, where we apply a suitable Gauss filter to lessen the influence of noise. Then apply the morphology operation to extract the inner and outer iris edge, determine the iris area. The proposed algorithm was tested using CASIA iris database(V1.0). And the experimental result shown the method was superior in processing speed under the same localization precision.
  • Keywords
    Gaussian processes; edge detection; feature extraction; filtering theory; image recognition; mathematical morphology; visual databases; CASIA iris database; Gaussian filtering; iris edge extraction; iris image preprocessing; iris localization scheme; iris recognition; morphological theory; Algorithm design and analysis; Filtering; Filters; Gaussian noise; Image databases; Iris recognition; Morphology; Noise shaping; Shape; Testing; iris recognition; localization; morphology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal-Image Technologies and Internet-Based System, 2007. SITIS '07. Third International IEEE Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3122-9
  • Type

    conf

  • DOI
    10.1109/SITIS.2007.39
  • Filename
    4618855