• DocumentCode
    1323993
  • Title

    Video-based signature verification and pen-grasping posture analysis for user-dependent identification authentication

  • Author

    Cheng, Hsu-Yung ; Lin, Chih-Lung ; Yu, Chih-Chang ; Gau, Vincent

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Chungli, Taiwan
  • Volume
    6
  • Issue
    5
  • fYear
    2012
  • Firstpage
    388
  • Lastpage
    396
  • Abstract
    This article proposes a video-based identification authentication framework via signature verification and pen-grasping posture analysis. The authors consider the case of using a camera instead of a pressure-sensitive tablet to acquire signatures. The proposed reliable verification method is useful when pressure-sensitive digitising tablets are not available. In addition, the authors can acquire more information in addition to the trajectories of the signature in video-based handwritten signature verification. The entire writing process and the pen-grasping posture are personalised features that cannot be easily imitated and forged. The authors analyse the signature trajectories using curvelets and the pen-grasping posture using modified motion energy images to perform user-dependent identification authentication. The proposed system is able to achieve both low false-rejection rates and low false-acceptance rates for database containing both unskilled and skilled imitation signatures.
  • Keywords
    cameras; curvelet transforms; handwriting recognition; image motion analysis; video signal processing; camera; curvelets; motion energy image; pen-grasping posture analysis; skilled imitation signature; unskilled imitation signature; user-dependent identification authentication; video-based handwritten signature verification; video-based identification authentication framework; writing process;
  • fLanguage
    English
  • Journal_Title
    Computer Vision, IET
  • Publisher
    iet
  • ISSN
    1751-9632
  • Type

    jour

  • DOI
    10.1049/iet-cvi.2010.0136
  • Filename
    6334791