• DocumentCode
    2280354
  • Title

    An overview of segmentation techniques for handwritten connected digits

  • Author

    Kulkarni, R.V. ; Vasambekar, P.N.

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Shivaji Univ., Vidyanagar, India
  • fYear
    2010
  • fDate
    15-17 Dec. 2010
  • Firstpage
    479
  • Lastpage
    482
  • Abstract
    Machine recognition of handwritten numerals has practical significance. Segmentation of connected digits is being recognized as a critical task in the field of document image analysis and recognition. Higher recognition rates for isolated digits Vs those obtained for connected numeral strings exemplify the vital role of connected digits segmentation. The present overview describes various segmentation techniques for connected digits in general numeral strings and mathematical expressions, worked out in this decade.
  • Keywords
    handwritten character recognition; image recognition; image segmentation; connected numeral string; document image analysis; handwritten connected digits; handwritten numeral; machine recognition; segmentation technique; Algorithm design and analysis; Artificial neural networks; Feature extraction; Handwriting recognition; Image segmentation; Reservoirs; Skeleton; connected digits; handwritten numerals; number recognition; segmentation; touching numerals;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Image Processing (ICSIP), 2010 International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4244-8595-6
  • Type

    conf

  • DOI
    10.1109/ICSIP.2010.5697522
  • Filename
    5697522