• DocumentCode
    3360497
  • Title

    Automated hand shape verification using HMM

  • Author

    Dong-Mei, Sun ; Zheng-Ding, Qiu

  • Author_Institution
    Inst. of Inf. Sci., Northern Jiaotong Univ., Beijing, China
  • Volume
    3
  • fYear
    2004
  • fDate
    31 Aug.-4 Sept. 2004
  • Firstpage
    2274
  • Abstract
    In this paper we present a method for identity verification based on matching of hand shapes. Our method first represents the shapes of hands by sets of ordered points. Then the contour of the hand is characterized by a features sequence consisting of two parameters: the radius and curvature at the contour points, MMM has proved a very successful tool for modeling and recognition sequence signal. So the hand shapes are compared using HMM. We apply a normalization score measurement to improve the classification ability and robustness. The experiment results show the effectiveness of our method and the correct verification rate can be above 90%.
  • Keywords
    hidden Markov models; image classification; image matching; image sequences; automated hand shape verification; contour points; features sequence; hand shape matching; normalization score measurement; recognition sequence signal; Biometrics; Fingerprint recognition; Fingers; Hidden Markov models; Iris; Retina; Robust control; Shape control; Size control; Sun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
  • Print_ISBN
    0-7803-8406-7
  • Type

    conf

  • DOI
    10.1109/ICOSP.2004.1442233
  • Filename
    1442233