• DocumentCode
    2011762
  • Title

    Off-Line Bangla Signature Verification

  • Author

    Pal, Srikanta ; Nguyen, Vu ; Blumenstein, Michael ; Pal, Umapada

  • Author_Institution
    Sch. of Inf. & Commun. Technol., Griffith Univ., Gold Coast, QLD, Australia
  • fYear
    2012
  • fDate
    27-29 March 2012
  • Firstpage
    282
  • Lastpage
    286
  • Abstract
    In the field of information security, biometric systems play an important role. Within biometrics, automatic signature identification and verification has been a strong research area because of the social and legal acceptance and extensive use of the written signature as an individual authentication. Signature verification is a process in which the questioned signature is examined in detail in order to determine whether it belongs to the claimed person or not. Despite substantial research in the field of signature verification involving Western signatures, very few works have been dedicated to non-Western signatures such as Chinese, Japanese, Arabic, or Persian etc. In this paper, the performance of an off-line signature verification system involving Bangla signatures, whose style is distinct from Western scripts, was investigated. The Gaussian Grid feature extraction technique was employed for feature extraction and Support Vector Machines (SVMs) were considered for classification. The Bangla signature database employed in the experiments consisted of 3000 forgeries and 2400 genuine signatures. An encouraging accuracy of 90.4% was obtained from the experiments.
  • Keywords
    feature extraction; handwriting recognition; natural language processing; support vector machines; visual databases; Arabic signature; Bangla signature database; Chinese signature; Gaussian grid feature extraction technique; Japanese signature; Persian signature; Western signature; authentication; feature extraction; information security; offline Bangla signature verification; signature identification; support vector machines; written signature; Databases; Educational institutions; Feature extraction; Forgery; Support vector machines; Training; Gaussian Grid feature; Offline verification systems; SVMs; authentication systems; biometrics; signature verification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis Systems (DAS), 2012 10th IAPR International Workshop on
  • Conference_Location
    Gold Cost, QLD
  • Print_ISBN
    978-1-4673-0868-7
  • Type

    conf

  • DOI
    10.1109/DAS.2012.60
  • Filename
    6195379