• DocumentCode
    317940
  • Title

    Recognition of handwritten Hindi numerals using structural descriptors

  • Author

    Elnagar, A. ; Al-Kharousi, F. ; Harous, S.

  • Author_Institution
    Dept. of Comput. Sci., Sultan Qaboos Univ., Muscat, Oman
  • Volume
    2
  • fYear
    1997
  • fDate
    12-15 Oct 1997
  • Firstpage
    983
  • Abstract
    A method for the recognition of handwritten Hindi numerals is proposed based on structural descriptors of numeral shapes. The method consists of three major steps: 1) preprocessing, where a handwritten numeral is scanned, normalized, and then thinned; 2) a robust algorithm is developed to segment the scanned numeral image into stroke(s), based on feature points; and 3) identify cavity features. The output of this algorithm is a syntactic representation (that is one or more syntactic terms) of the scanned numeral. Finally, the syntactic representation is matched against a set of syntactic representation prototypes of handwritten numerals and the recognition result is reported. Early experimental results are encouraging and prove the tolerance of the proposed system to recognize a high variability of numeral shapes
  • Keywords
    character recognition; feature extraction; image representation; image segmentation; parallel algorithms; character recognition; feature extraction; feature points; handwritten Hindi numerals; parallel algorithm; preprocessing; segmentation; structural descriptors; syntactic representation; thinning; Character recognition; Computer science; Educational institutions; Handwriting recognition; Image segmentation; Natural languages; Postal services; Robustness; Shape; Text recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-4053-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1997.638075
  • Filename
    638075