• DocumentCode
    2953724
  • Title

    A new approach for context-independent handwritten offline diagram recognition using support vector machines

  • Author

    Refaat, Khaled S. ; Helmy, Wael N. ; Ali, AbdelRahman H. ; AbdelGhany, Mohamed S. ; Atiya, Amir F.

  • Author_Institution
    Comput. Eng. Dept., Cairo Univ., Cairo
  • fYear
    2008
  • fDate
    1-8 June 2008
  • Firstpage
    177
  • Lastpage
    182
  • Abstract
    Structured diagrams are very prevalent in many document types. Most people who need to create such diagrams use structured graphics editors such as Microsoft Visio. Structured graphics editors are extremely powerful and expressive but they can be cumbersome to use. We have shown through extensive timing experiments that structured diagrams drawn by hand will take only about 10% of the time it takes to draw one using a tool like Visio. This indicates the value of automated recognition of hand-written diagrams. Recently, applications have been developed that use online systems running on pen-input PCs that allow users to create structured diagrams by drawing the diagram on the PC tablet. The progress of offline diagram recognition is still minimal. The objective of this paper is to propose a context-independent off-line diagram recognition system. Our approach utilizes support vector machines for recognition and line primitive extraction by interpretation of line continuation for segmentation.
  • Keywords
    handwritten character recognition; image segmentation; support vector machines; Microsoft Visio; context-independent handwritten offline diagram recognition; structured graphics editors; support vector machines; Handwriting recognition; Neural networks; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1820-6
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2008.4633786
  • Filename
    4633786