• DocumentCode
    1582929
  • Title

    Adaptive technology for mail-order form segmentation

  • Author

    Belaid, Abdel ; Belaid, A. ; Valverde, Late N. ; Kébairi, S.

  • Author_Institution
    LORIA-CNRS, Vandoeuvre-les-Nancy, France
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    689
  • Lastpage
    693
  • Abstract
    In this paper, an approach for adaptive region segmentation of mail-order forms for high volume application is described. Regions are first identified through a selection of their anchor points described by a constraint graph, illustrating their typographic aspects in the nodes, and their topographical relationships in the arcs. Then the identification of the actual anchor points is performed from a list of textual candidates, using the Arc Consistency Algorithm (AC4). Finally, some contextual heuristics are investigated for properly delimiting the regions. The originality of this approach lies mainly in the absence of a rigid a priori model, replaced by a simple and reliable association of anchor points. The constraint graph used for their description can be easily derived from a general logical definition of their content. Experimental results are overall encouraging and the methodology integration is under execution for commercialization
  • Keywords
    document image processing; image segmentation; optical character recognition; Arc Consistency Algorithm; OCR; adaptive region segmentation; adaptive technology; anchor points; constraint graph; contextual heuristics; experimental results; mail-order form segmentation; topographical relationships; typographic aspects; Advertising; Business; Face recognition; Filling; IEEE news; Insurance; Marketing and sales; Vehicles; Writing; Zirconium;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7695-1263-1
  • Type

    conf

  • DOI
    10.1109/ICDAR.2001.953878
  • Filename
    953878