• DocumentCode
    1633185
  • Title

    Segmentation of Arabic Handwriting Based on both Contour and Skeleton Segmentation

  • Author

    Wshah, Safwan ; Shi, Zhixin ; Govindaraju, Venu

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. at Buffalo, Amherst, NY, USA
  • fYear
    2009
  • Firstpage
    793
  • Lastpage
    797
  • Abstract
    We propose a new algorithm for segmentation of off-line handwritten Arabic words. The algorithm segments the connected letters to smaller segments each of which contains no more than three letters. Each letter may be segmented to at most five pieces. In addition to improving the recognition of Arabic words, another potential application of the proposed segmentation method is to build lexicon of small size, consisting of no more than three letter combinations. Generally, it is very hard to generate lexicon for recognition of unconstraint handwritten Arabic documents due to the large number of words of Arabic language.The algorithm has been tested on over 6300 words from 45 different documents written by 18 writers. The system is able to segment more than 93% of the words into segments, each containing at most one letter, 6% of the words into segments that contains two letters and 3% of the words into segments that contains three letters.
  • Keywords
    document image processing; handwriting recognition; image recognition; image segmentation; natural languages; word processing; Arabic handwriting recognition; handwritten Arabic document; off-line handwritten Arabic word; skeleton segmentation; Algorithm design and analysis; Character recognition; Computer science; Handwriting recognition; Robustness; Shape; Skeleton; Testing; Text analysis; Venus; Arabic OCR; Arabic characters segmentation; Arabic handwritten segmentation; Arabic segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1520-5363
  • Print_ISBN
    978-1-4244-4500-4
  • Electronic_ISBN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2009.152
  • Filename
    5277512