• DocumentCode
    1638255
  • Title

    Improving the Enrollment in Dynamic Signature Verfication with Synthetic Samples

  • Author

    Galbally, Javier ; Fierrez, Julian ; Martinez-Diaz, Marcos ; Ortega-Garcia, Javier

  • Author_Institution
    Biometric Recognition Group, Univ. Autonoma de Madrid, Madrid, Spain
  • fYear
    2009
  • Firstpage
    1295
  • Lastpage
    1299
  • Abstract
    A novel scheme to generate multiple synthetic samples from a real on-line handwritten signature is proposed. The algorithm models a transmission channel which introduces a certain distortion into the real signature to produce the different synthetic samples. The method is used to increase the amount of data of the clients enrolling on a state-of-the-art HMM-based signature verification system. The enhanced enrollment results in performance improve up to70% between the case in which only one real sample of the user was available for the training, and the case where the proposed algorithm was used to generate additional synthetic training data.
  • Keywords
    handwriting recognition; hidden Markov models; dynamic signature verification; hidden Markov model; online handwritten signature; synthetic samples; Attenuation; Bioinformatics; Biometrics; Fingerprint recognition; Handwriting recognition; Hidden Markov models; Iris; Speech synthesis; Text analysis; Training data; On-line signature verification; enrollment; synthetic generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1520-5363
  • Print_ISBN
    978-1-4244-4500-4
  • Electronic_ISBN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2009.38
  • Filename
    5277701