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. 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. MOTS-CLES : operateur de position1, reconnaissance de la structure de document2, interaction utilisateur3, apprentissage de positionnement4.
['Cérès Carton', 'Aurélie Lemaitre', 'Bertrand Coüasnon']
LearnPos : un nouvel outil pour l'apprentissage interactif de positionnement