Document Image Segmentation Using a 2D Conditional Random Field Model

Curitiba, Parana, Brazil September 23-September 26

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http://doi.ieeecomputersociety.org/10.1109/ICDAR.2007.102

Ninth International Conference on Doc ...

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	ASCII Text	x
	S. Nicolas, J. Dardenne, T. Paquet, L. Heutte, "Document Image Segmentation Using a 2D Conditional Random Field Model," Document Analysis and Recognition, International Conference on, vol. 1, pp. 407-411, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1, 2007.

	BibTex	x
	@article{ 10.1109/ICDAR.2007.102, author = {S. Nicolas and J. Dardenne and T. Paquet and L. Heutte}, title = {Document Image Segmentation Using a 2D Conditional Random Field Model}, journal ={Document Analysis and Recognition, International Conference on}, volume = {1}, year = {2007}, issn = {1520-5363}, pages = {407-411}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2007.102}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Document Analysis and Recognition, International Conference on TI - Document Image Segmentation Using a 2D Conditional Random Field Model SN - 1520-5363 SP407 EP411 A1 - S. Nicolas, A1 - J. Dardenne, A1 - T. Paquet, A1 - L. Heutte, PY - 2007 VL - 1 JA - Document Analysis and Recognition, International Conference on ER -

S. Nicolas, Laboratoire LITIS EA, France

J. Dardenne, Universit? de Rouen, France

T. Paquet, Laboratoire LITIS EA

L. Heutte, Laboratoire LITIS EA

This work relates to the implementation of a 2D conditional random field model in the context of document image analysis. Our model makes it possible to take variability into account and to integrate contextual knowledge, while taking benefit from machine learning techniques. Experiments on handwritten drafts of Flaubert show that these models provide interesting solutions.

Citation:

S. Nicolas, J. Dardenne, T. Paquet, L. Heutte, "Document Image Segmentation Using a 2D Conditional Random Field Model," icdar, vol. 1, pp.407-411, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1, 2007

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