• DocumentCode
    2018999
  • Title

    Adaptive dissection based subword segmentation of printed Arabic text

  • Author

    Zidouri, A. ; Sarfraz, M. ; Shahab, S.A. ; Jafri, S.M.

  • Author_Institution
    Dept. of Electr. Eng., King Fahd Univ. of Pet. & Minerals, Dhahran, Saudi Arabia
  • fYear
    2005
  • fDate
    6-8 July 2005
  • Firstpage
    239
  • Lastpage
    243
  • Abstract
    Numerous segmentation and recognition techniques have been proposed in literature for Arabic OCR system. Correct and efficient segmentation of Arabic text into characters is considered to be a fundamental problem. While OCR systems for other languages do not need segmentation for printed text for successful recognition, it is essential to design robust and powerful segmentation algorithms or employ segmentation free recognition schemes for printed Arabic text. Even more, in recognition of handwritten characters, segmentation is considered to be indispensable. Most of current segmentation technique suffers from over segmentation and under segmentation in addition to not being adaptive in nature. In this paper, we have proposed a new sub-word segmentation scheme, which is independent of font size and font type.
  • Keywords
    adaptive systems; handwritten character recognition; image segmentation; natural languages; optical character recognition; text analysis; Arabic OCR system; adaptive dissection based subword segmentation; printed Arabic text; Algorithm design and analysis; Character recognition; Computer science; Handwriting recognition; Minerals; Optical character recognition software; Petroleum; Prototypes; Robustness; Text recognition; Arabic Character Recognition; Word Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Visualisation, 2005. Proceedings. Ninth International Conference on
  • ISSN
    1550-6037
  • Print_ISBN
    0-7695-2397-8
  • Type

    conf

  • DOI
    10.1109/IV.2005.17
  • Filename
    1509085