Markov Random Field Models to Extract The Layout of Complex Handwritten Documents

Stéphane Nicolas 1 Thierry Paquet 1 Laurent Heutte 1
1 PSI - Perception, Systèmes, Information
Abstract : We consider in this paper the problem of complex handwritten page segmentation such as novelist drafts or authorial manuscripts. We propose to use stochastic and contextual models in order to cope with local spatial variability, and to take into account some prior knowledge about the global structure of the document image. The models we propose to use are Markov Random Field models. Using this model, the segmentation is performed using optimization techniques. Using the MRF framework, the segmentation is equivalent to an image labeling problem and is performed using optimization techniques.
Keywords : Document image analysis layout extraction Markov radom field image labeling
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Communication dans un congrès
Guy Lorette. Tenth International Workshop on Frontiers in Handwriting Recognition, Oct 2006, La Baule (France), Suvisoft, 2006
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Dernière modification le : mardi 5 juin 2018 - 10:14:21
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  • HAL Id : inria-00104788, version 1

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Stéphane Nicolas, Thierry Paquet, Laurent Heutte. Markov Random Field Models to Extract The Layout of Complex Handwritten Documents. Guy Lorette. Tenth International Workshop on Frontiers in Handwriting Recognition, Oct 2006, La Baule (France), Suvisoft, 2006. 〈inria-00104788〉

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