• DocumentCode
    2001596
  • Title

    Unconstrained Arabic Handwritten Word Feature Extraction: A Comparative Study

  • Author

    AlKhateeb, Jawad H. ; Ren, Jinchang ; Jiang, Jianmin ; Ipson, Stan S.

  • Author_Institution
    Digital Media & Syst. Res. Inst., Univ. of Bradford, Bradford
  • fYear
    2009
  • fDate
    27-29 April 2009
  • Firstpage
    1655
  • Lastpage
    1656
  • Abstract
    This paper presents an overview of feature extraction techniques for unconstrained Arabic handwritten word recognition. Choosing a technique for extraction the features considers the most important factor in achieving high recognition rates in word or character recognition. Different techniques were designed to extract the features from the Arabic words. These techniques are presented and discussed in terms of invariant invariance properties.
  • Keywords
    feature extraction; handwritten character recognition; character recognition; invariant invariance properties; unconstrained arabic handwritten word feature extraction; Application software; Character recognition; Discrete cosine transforms; Feature extraction; Hidden Markov models; Image recognition; Image segmentation; Optical character recognition software; Skeleton; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology: New Generations, 2009. ITNG '09. Sixth International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4244-3770-2
  • Electronic_ISBN
    978-0-7695-3596-8
  • Type

    conf

  • DOI
    10.1109/ITNG.2009.222
  • Filename
    5070888
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2001596