• DocumentCode
    3269364
  • Title

    An Iris Recognition Approach based on Fuzzy Support Vector Machine

  • Author

    Gu, Hongying ; Gao, Zhiwen ; Yang, Cheng

  • Author_Institution
    Inst. of Artificial Intell., Zhejiang Univ., Hangzhou, China
  • Volume
    2
  • fYear
    2011
  • fDate
    18-21 Dec. 2011
  • Firstpage
    370
  • Lastpage
    373
  • Abstract
    An iris recognition system named IrisPassport is presented in this paper. Standard Deviation is used to localize the irises from iris images. After localization, IrisPassport uses Steerable Pyramid and Variant Fractal Dimension as features with orientation information. Aiming to build a robust solution for non-cooperative iris images, we adopt fuzzy support vector machine (FSVM) because we consider different samples contributes to classification differently and a member function can be used when unclassifiable regions appear. Experimental data demonstrates the potential of our new approach, and shows that it performs favorably when compared with the former algorithms.
  • Keywords
    fuzzy set theory; iris recognition; support vector machines; IrisPassport; SVM; fuzzy support vector machine; iris recognition approach; member function; noncooperative iris images; orientation information; standard deviation; steerable pyramid dimension; variant fractal dimension; Educational institutions; Fractals; Image databases; Iris; Iris recognition; Support vector machines; Training; fuzzy support vector machine; iris recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    978-1-4577-2134-2
  • Type

    conf

  • DOI
    10.1109/ICMLA.2011.169
  • Filename
    6147708