• DocumentCode
    2785411
  • Title

    A hybrid approach to character segmentation of Gurmukhi script characters

  • Author

    Davessar, Neena Madan ; Madan, Sunil ; Singh, Hardeep

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Guru Nanak Dev Univ., Amritsar, India
  • fYear
    2003
  • fDate
    15-17 Oct. 2003
  • Firstpage
    169
  • Lastpage
    173
  • Abstract
    A new approach to segmentation of machine printed Gurmukhi text has been suggested. This approach can easily be extended to other Indian language scripts such as Devnagri and Bangla. Most of the characters in these scripts have horizontal lines at the top called headlines. Besides, there are cases in which the characters are found touching in the scanned image, just below the headline. To resolve these issues, a two-pass mechanism is used. In pass-one it approximates the segmentation point, while in pass-two the cutting point is optimized. This approach has been very successful in segmenting a pair as well as triplets of touching characters.
  • Keywords
    image segmentation; natural languages; optical character recognition; Bangla; Devnagri; Gurmukhi script characters; Indian language scripts; character segmentation; cutting point optimization; horizontal headlines; machine printed Gurmukhi text; segmentation point approximation; two pass mechanism; Banking; Character recognition; Conferences; Error analysis; Image recognition; Image segmentation; Office automation; Optical character recognition software; Pattern recognition; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. 32nd
  • Print_ISBN
    0-7695-2029-4
  • Type

    conf

  • DOI
    10.1109/AIPR.2003.1284267
  • Filename
    1284267