A Markovian Approach for Handwritten Document Segmentation

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18th International Conference on Pattern Recognition (ICPR'06) Volume 3

Hong Kong

August 20-August 24

ISBN: 0-7695-2521-0

	ASCII Text	x
	St?phane Nicolas, Thierry Paquet, Laurent Heutte, "A Markovian Approach for Handwritten Document Segmentation," Pattern Recognition, International Conference on, vol. 3, pp. 292-295, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006.

	BibTex	x
	@article{ 10.1109/ICPR.2006.94, author = {St?phane Nicolas and Thierry Paquet and Laurent Heutte}, title = {A Markovian Approach for Handwritten Document Segmentation}, journal ={Pattern Recognition, International Conference on}, volume = {3}, year = {2006}, issn = {1051-4651}, pages = {292-295}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.94}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - A Markovian Approach for Handwritten Document Segmentation SN - 1051-4651 SP292 EP295 A1 - St?phane Nicolas, A1 - Thierry Paquet, A1 - Laurent Heutte, PY - 2006 KW - null VL - 3 JA - Pattern Recognition, International Conference on ER -

St?phane Nicolas, Laboratoire LITIS - Universit? de Rouen, cedex, FRANCE

Thierry Paquet, Laboratoire LITIS - Universit? de Rouen, cedex, FRANCE

Laurent Heutte, Laboratoire LITIS - Universit? de Rouen, cedex, FRANCE

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.94

We address in this paper the problem of segmenting complex handritten pages 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.

Citation:

St?phane Nicolas, Thierry Paquet, Laurent Heutte, "A Markovian Approach for Handwritten Document Segmentation," icpr, vol. 3, pp.292-295, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006

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