• DocumentCode
    2219978
  • Title

    Bit plane decomposition and the scanning n-tuple classifier

  • Author

    Hoque, S. ; Sirlantzis, K. ; Fairhurst, M.C.

  • Author_Institution
    Dept. of Electron., Kent Univ., Canterbury, UK
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    207
  • Lastpage
    211
  • Abstract
    This paper describes a multiple classifier configuration for high performance off-line handwritten character recognition applications. Along with a conventional scanning n-tuple classifier (or sn-tuple) implementation, three other sn-tuple systems have been used which are trained using a binary feature set extracted from the contour chain-codes using a novel decomposition technique. The overall accuracy thus achievable by the proposed scheme is much higher than most other classification systems available and the added complexity (over conventional sn-tuple system) is minimal.
  • Keywords
    computational complexity; feature extraction; handwritten character recognition; image classification; binary feature set; bit plane decomposition; contour chain-codes; decomposition technique; high-performance off-line handwritten character recognition; multiple classifier configuration; scanning n-tuple classifier; sn-tuple implementation; Character recognition; Electronic mail; Feature extraction; Fusion power generation; Handwriting recognition; Humans; Image coding; Image recognition; Image segmentation; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Frontiers in Handwriting Recognition, 2002. Proceedings. Eighth International Workshop on
  • Print_ISBN
    0-7695-1692-0
  • Type

    conf

  • DOI
    10.1109/IWFHR.2002.1030910
  • Filename
    1030910