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Proceedings Paper

LearnPos: a new tool for interactive learning positioning
Author(s): Cérès Carton; Aurélie Lemaitre; Bertrand Coüasnon
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Paper Abstract

The analysis of 2D structured documents often requires localizing data inside of a document during the recognition process. In this paper we present LearnPos a new generic tool, independent of any document recognition system. LearnPos models and evaluates positioning from a learning set of documents. Thanks to LearnPos, the user is helped to define the physical structure of the document. He then can concentrate his efforts on the definition of the logical structure of the documents. LearnPos is able to furnish spatial information for both absolute and relative spatial relations, in interaction with the user. Our method can handle spatial relations compose of distinct zones and is able to furnish appropriate order and point of view to minimize errors. We prove that resulting models can be successfully used for structured document recognition, while reducing the manual exploration of the data set of documents.

Paper Details

Date Published: 24 March 2014
PDF: 12 pages
Proc. SPIE 9021, Document Recognition and Retrieval XXI, 90210H (24 March 2014); doi: 10.1117/12.2042379
Show Author Affiliations
Cérès Carton, Univ. Européenne de Bretagne, IRISA / INSA de Rennes (France)
Aurélie Lemaitre, Univ. Européenne de Bretagne, IRISA, Univ. Rennes 2 (France)
Bertrand Coüasnon, Institut National des Sciences Appliquées de Rennes (France)

Published in SPIE Proceedings Vol. 9021:
Document Recognition and Retrieval XXI
Bertrand Coüasnon; Eric K. Ringger, Editor(s)

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