• DocumentCode
    2726622
  • Title

    On-line Signature Verification: An Approach Based on Cluster Representations of Global Features

  • Author

    Guru, D.S. ; Prakash, H.N. ; Manjunath, S.

  • Author_Institution
    Dept. of Studies in Comput. Sci., Univ. of Mysore, Mysore
  • fYear
    2009
  • fDate
    4-6 Feb. 2009
  • Firstpage
    209
  • Lastpage
    212
  • Abstract
    In this paper, we propose a new method of representation of on-line signatures by clustering of signatures. Our idea is to provide better representation by clustering of signatures based on global features. Global features of signatures of each cluster are used to form an interval valued feature vector which is a symbolic representation for a cluster. Based on cluster representation, we propose methods of signature verification. We compare the feasibility of the proposed representation scheme for signature verification on a large MCYT_ signature database of 16500 signatures. Unlike other signature verification methods, the proposed method is simple and efficient and in addition, shows a remarkable reduction in EER.
  • Keywords
    handwriting recognition; image representation; image segmentation; pattern clustering; vectors; feature dependent threshold; global feature clustering; interval valued feature vector; online signature representation; online signature verification; symbolic representation; Computer science; Data analysis; Fuzzy neural networks; Handwriting recognition; Hidden Markov models; Neural networks; Pattern recognition; Shape; Spatial databases; Support vector machines; Fuzzy C-means (FCM) clustering; Global features; On-line signature verification; Symbolic feature vector;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Pattern Recognition, 2009. ICAPR '09. Seventh International Conference on
  • Conference_Location
    Kolkata
  • Print_ISBN
    978-1-4244-3335-3
  • Type

    conf

  • DOI
    10.1109/ICAPR.2009.30
  • Filename
    4782776