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Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1
Document Image Segmentation Using a 2D Conditional Random Field Model
Curitiba, Parana, Brazil
September 23-September 26
ISBN: 0-7695-2822-8
ASCII Text
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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
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@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
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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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