• DocumentCode
    3167015
  • Title

    A Front-End OCR for Omni-Font Persian/Arabic Cursive Printed Documents

  • Author

    Mehran, Ramin ; Pirsiavash, Hamed ; Razzazi, Farbod

  • Author_Institution
    K.N.Toosi University of Technology and Paya Soft Co.
  • fYear
    205
  • fDate
    6-8 Dec. 205
  • Firstpage
    56
  • Lastpage
    56
  • Abstract
    Compared to non-cursive scripts, optical character recognition of cursive documents comprises extra challenges in layout analysis as well as recognition of the printed scripts. This paper presents a front-end OCR for Persian/Arabic cursive documents, which utilizes an adaptive layout analysis system in addition to a combined MLP-SVM recognition process. The implementation results on a comprehensive database show a high degree of accuracy which meets the requirements of commercial use.
  • Keywords
    Adaptive systems; Character recognition; Databases; Learning systems; Machine learning; Optical character recognition software; Shape; Solids; Speech recognition; Text analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Image Computing: Techniques and Applications, 2005. DICTA '05. Proceedings 2005
  • Conference_Location
    Queensland, Australia
  • Print_ISBN
    0-7695-2467-2
  • Type

    conf

  • DOI
    10.1109/DICTA.2005.3
  • Filename
    1587658
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3167015