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
Link To Document :
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