• DocumentCode
    1582570
  • Title

    A graph-based segmentation and feature extraction framework for Arabic text recognition

  • Author

    Elgammal, Ahmed M. ; Ismail, Mohamed A.

  • Author_Institution
    Dept. of Comput. Sci., Maryland Univ., College Park, MD, USA
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    622
  • Lastpage
    626
  • Abstract
    This paper presents a graph-based framework for the segmentation of Arabic text. The same framework is used to extract font independent structural features from the text that are used in the recognition. The major contribution of this paper is a new graph-based structural segmentation approach based on the topological relation between the baseline and the line adjacency graph representation of the text. The text is segmented to sub-character units that we call "scripts". A structure analysis approach is used for recognition of these units. A different classifier is used to recognize dots and diacritic signs. The final character recognition is achieved by using a regular grammar that describes how characters are composed from scripts
  • Keywords
    character recognition; edge detection; feature extraction; graph theory; image segmentation; Arabic text recognition; baseline detection; character recognition; feature extraction; line adjacency graph; regular grammar; script segmentation; Character recognition; Computer science; Educational institutions; Error analysis; Feature extraction; Optical character recognition software; Structural shapes; Text recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7695-1263-1
  • Type

    conf

  • DOI
    10.1109/ICDAR.2001.953864
  • Filename
    953864