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Logical Labeling using Bayesien Networks

Souad Bensafi, Marc Parizeau, Franck Lebourgeois and Hubert Emptoz

Abstract - This paper discusses logical labeling in documents, which is one basic step in logical structure recognition. Logical labels have to be attributed to text blocks composing the layout structure. Our study is based on physical characteristics having a visual aspect: typographic, geometric and/or topologic attributes. Our objective is to map a low level logical structure, which consists of a set of logical labels, on the extracted layout structure components. We have to build a model that allows this mapping. However, the documents we consider have various layout and logical structures, thus, we chose to perform this task by supervised learning on the basis of a set of training documents. This allows us to de ne a generic method to solve this problem, without imposing any constraint on document structure. We propose a probabilistic model represented by a Bayesian Network (BN), which is a graphical model used in our problem as a classi er. A prototype has been implemented, and applied to tables of contents in periodics.

Bibtex:

@inproceedings{Bensafi47,
author    = { Souad Bensafi and Marc Parizeau and Franck Lebourgeois and Hubert Emptoz },
title     = { Logical Labeling using Bayesien Networks },
booktitle = { Proc. of the International Conference on Document Analysis and Recognition (ICDAR) },
pages     = { 832-836 },
year      = { 2001 },
month     = { September 10-13 }
}

Dernière modification: 2002/06/14 par parizeau

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