• DocumentCode
    3146866
  • Title

    Authorship Invarianceness for Writer Identification

  • Author

    Muda, Azah Kamilah ; Shamsuddin, Siti Mariyam ; Abraham, Ajith

  • Author_Institution
    Univ. Teknikal Malaysia Melaka, Ayer Keroh, Malaysia
  • fYear
    2009
  • fDate
    25-28 June 2009
  • Firstpage
    34
  • Lastpage
    39
  • Abstract
    The uniqueness of shape and style of handwriting can be used for authorpsilas authentication. Acquiring individual features to obtain authorship invariance-ness concept have led to an important research in writer identification domain. This paper discusses the investigation of this concept by extracting individual features using geometric moment function. Experiment results have shown that handwriting invarianceness are discerning with better identification accuracy. This has verified that moment function is worth to be explored in identifying the handwritten authorship for writer identification.
  • Keywords
    feature extraction; geometry; handwriting recognition; author authentication; authorship invarianceness; feature extraction; geometric moment function; handwriting invarianceness; handwriting shape; handwriting style; writer identification; Analysis of variance; Authentication; Biometrics; Computational complexity; Feature extraction; Forensics; Machine intelligence; Shape; Spatial databases; Writing; Authorship Invarianceness; Identification; Moment Function;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biometrics and Kansei Engineering, 2009. ICBAKE 2009. International Conference on
  • Conference_Location
    Cieszyn
  • Print_ISBN
    978-0-7695-3692-7
  • Electronic_ISBN
    978-0-7695-3692-7
  • Type

    conf

  • DOI
    10.1109/ICBAKE.2009.13
  • Filename
    5223273