• DocumentCode
    3319971
  • Title

    Numeral characters and capital letters segmentation recognition in mixed handwriting context

  • Author

    Wehbi, H. ; Oulhadj, H. ; Lemoine, J. ; Petit, E.

  • Author_Institution
    LERISS, Paris XII Univ., Val-de-Marne, France
  • Volume
    2
  • fYear
    1995
  • fDate
    14-16 Aug 1995
  • Firstpage
    878
  • Abstract
    For the analytic on-line recognition of handwriting, the range of pattern recognition problems can be described by the severity of letter segmentation required. More difficult problems require an interaction of letter segmentation and recognition. These problems include overlapping discretely written characters, pure cursive writing, and mixed cursive and discrete writing. To these problems concerning the letter segmentation, the word segmentation problems is added. Since a script can contain numbers, capital letters as well as lowercase letters, it is necessary to have a system able to recognize them. This paper describes an on-line system for identifying and recognizing numeral characters and capital letters in handwriting sentences. This system provides two segmentation modules: the first one is to isolate the word drawings within a sentence, and the other one is to separate numeral characters and capital letters from a mixed writing prior to their recognition
  • Keywords
    handwriting recognition; image segmentation; optical character recognition; analytic on-line recognition; capital letters segmentation recognition; mixed handwriting context; mixed writing; numeral characters segmentation recognition; overlapping discretely written characters; pure cursive writing; word drawings; word segmentation problems; Character recognition; Data acquisition; Data mining; Feature extraction; Filtering; Filters; Handwriting recognition; Shape; Tag clouds; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    0-8186-7128-9
  • Type

    conf

  • DOI
    10.1109/ICDAR.1995.602041
  • Filename
    602041