• DocumentCode
    1883330
  • Title

    Computational intelligence techniques for reflections identification in iris biometric images

  • Author

    Scotti, Fabio

  • Author_Institution
    Univ. of Milan, Crema
  • fYear
    2007
  • fDate
    27-29 June 2007
  • Firstpage
    84
  • Lastpage
    88
  • Abstract
    Iris biometric systems identify individuals by comparing the characteristics of the iris acquired by the acquisition sensors. When reflections are present in the iris image, the portion of the image covered by reflections must be discarded from any further comparison since it can produce false matches. The paper presents a methodology for reflections identification in iris biometric images based on neural networks. In particular, this paper proposes a set of features which can be extracted from the iris image and that can be effectively used to achieve an accurate identification of the reflection position using a neural network Moreover, the paper presents how the radial symmetry operator can be used as a proper feature to identify the reflections in iris images. The method is general and can be used in any biometric system based on iris images.
  • Keywords
    biometrics (access control); eye; feature extraction; image recognition; medical image processing; neural nets; computational intelligence techniques; feature extraction; iris biometric images; neural networks; radial symmetry operator; reflections identification; Biometrics; Biosensors; Cameras; Computational intelligence; Eyelids; Image sensors; Iris; Neural networks; Optical reflection; Optical sensors; Biometric System; Iris; Neural Networks; Radial symmetry;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Measurement Systems and Applications, 2007. CIMSA 2007. IEEE International Conference on
  • Conference_Location
    Ostuni
  • Print_ISBN
    978-1-4244-0824-5
  • Electronic_ISBN
    978-1-4244-0824-5
  • Type

    conf

  • DOI
    10.1109/CIMSA.2007.4362544
  • Filename
    4362544