[1]
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V. Rabeux, N. Journet, A. Vialard, and J.-P. Domenger.
Quality evaluation of degraded document images for binarization
result prediction.
International Journal on Document Analysis and Recognition
(IJDAR), 17(2):125-137, 2014.
[ bib ]
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[2]
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D. Coeurjolly, A. Montanvert, and J.-M. Chassery, editors.
Géométrie discrète et images numériques, chapter Attributs de
bord.
Traité IC2, Signal et Image. Hermès, Paris, 2007.
[ bib ]
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[3]
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J.-O. Lachaud, A. Vialard, and F. de Vieilleville.
Fast, accurate and convergent tangent estimation on digital contours.
Image and Vision Computing, 25(10):1572-1587, October 2007.
[ bib ]
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[4]
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J.-P. Braquelaire and A. Vialard.
Euclidean paths: a new representation of boundary of discrete
regions.
Graphical Models and Image Processing, 61(1):16-43, 1999.
[ bib ]
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[5]
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J.-P. Braquelaire and A. Vialard.
A new antialiasing approach for image compositing.
Visual Computer, 13(5):218-227, 1997.
[ bib ]
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[1]
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O. Augereau, N. Journet, A. Vialard, and J.-P. Domenger.
Improving classification of an industrial document image database by
combining visual and textual features.
In Proceedings of the 11th IAPR International Workshop on
Document Analysis Systems, 2014.
[ bib ]
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[2]
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V. Rabeux, N. Journet, A. Vialard, and J.-P. Domenger.
Quality evaluation of ancient digitized documents for binarization
prediction.
In Proceedings of the International Conference on Document Image
Analysis and Recognition, 2013.
[ bib ]
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[3]
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V. Rabeux, N. Journet, A. Vialard, and J.-P. Domenger.
Document perceptual quality ground truth creation.
In Proceedings of the 10th IAPR International Workshop on
Document Analysis Systems, 2012.
[ bib ]
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[4]
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N.Journet, A. Vialard, and J.-P. Domenger.
Analyse de fontes anciennes : de la génération de données
synthétiques à la reconnaissance.
In Actes du Colloque International Francophone sur l'écrit et du
Document (CIFED 2010), Sousse, 2010.
[ bib ]
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[5]
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S. Marchand, P. Desbarats, A. Vialard, F. Bechtel, A. Ben Amara, B. Cicuttini,
J.-P. Bost, A. Bresson, K. Konuk, and A. Beurivé.
Ibisa: Image-based identification / search for archaeology.
In Proceedings of the 10th International Symposium on Virtual
Reality, Archaeology and Cultural Heritage (VAST'09), Malta, 2009.
[ bib ]
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[6]
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S. Marchand and A. Vialard.
The hough transform for binaural source localization.
In Proceedings of the Digital Audio Effects (DAFx'09)
Conference, Como, Italy, 2009.
[ bib ]
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[7]
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J.-O. Lachaud, A. Vialard, and F. de Vieilleville.
Analysis and comparative evaluation of discrete tangent estimators.
In E. Andrès, G. Damiand, and P. Lienhardt, editors, Proc.
Int. Conf. Discrete Geometry for Computer Imagery (DGCI'2005), Poitiers,
France, volume 3429 of LNCS, pages 140-251. Springer, 2005.
[ bib ]
Keywords: discrete geometry, discrete tangent estimators, digital straight segments
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[8]
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J.-O. Lachaud and A. Vialard.
Geometric measures on arbitrary dimensional digital surfaces.
In G. Sanniti di Baja, S. Svensson, and I. Nyström, editors,
Proc. Int. Conf. Discrete Geometry for Computer Imagery (DGCI'2003), Napoli,
Italy, volume 2886 of LNCS, pages 434-443. Springer, 2003.
[ bib ]
Keywords: digital topology, cellular decomposition, digital surface tracking, discrete geometry, discrete normal estimator
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[9]
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J.-O. Lachaud and A. Vialard.
Discrete deformable boundaries for the segmentation of
multidimensional images.
In C. Arcelli, L. P. Cordella, and G. Sanniti di Baja, editors,
Proc. 4th Int. Workshop on Visual Form (IWVF4), Capri, Italy, volume 2059 of
Lecture Notes in Computer Science, pages 542-551. Springer-Verlag,
2001.
[ bib ]
Energy-minimizing techniques are an interesting approach to the
segmentation problem. They extract image components by deforming a
geometric model according to energy constraints. This paper proposes
an extension to these works, which can segment arbitrarily complex
image components in any dimension. The geometric model is a digital
surface with which an energy is associated. The model grows inside the
component to segment by following minimal energy paths. The
segmentation result is obtained a posteriori by examining the
energies of the successive model shapes. We validate our approach on
several 2D images.
Keywords: image segmentation, discrete deformable model, energy-minimization, digital surface
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[10]
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A. Vialard.
Euclidean paths for representing and transforming scanned characters.
In K. Tombre and A. Chhabra, editors, Proc. 2nd IAPR Int.
Workshop on Graphics Recognition (GREC'97), Nancy, France, volume 1389 of
Lecture Notes in Computer Science, pages 58-67. Springer-Verlag, 1997.
[ bib ]
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[11]
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A. Vialard.
Geometrical parameters extraction from discrete paths.
In S. Miguet, A. Montanvert, and S. Ubéda, editors, Proc. 6th
Discrete Geometry for Computer Imagery (DGCI'96), Lyon, France, volume 1176
of Lecture Notes in Computer Science, pages 24-35. Springer-Verlag,
1996.
[ bib ]
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[12]
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J.-P.Braquelaire, L. Brun, and A. Vialard.
Inter-pixel euclidean paths for image analysis.
In S. Miguet, A. Montanvert, and S. Ubéda, editors, Proc. 6th
Discrete Geometry for Computer Imagery (DGCI'96), Lyon, France, volume 1176
of Lecture Notes in Computer Science, pages 193-204. Springer-Verlag,
1996.
[ bib ]
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[1]
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J.-O. Lachaud et A. Vialard A. Esnard.
Discrete deformable boundaries for 3d image segmentation.
Research Report 1270-02, LaBRI, University Bordeaux 1, Talence,
France, 2002.
[ bib ]
|
[2]
|
J.-O. Lachaud and A. Vialard.
Discrete deformable boundaries for image segmentation.
Research Report 1244-00, LaBRI, Talence, France, 2000.
[ bib ]
Energy-minimizing techniques are an interesting approach to the
segmentation problem. They extract image components by deforming a
geometric model according to energy constraints. This paper proposes
an extension to these works, which can segment arbitrarily complex
image components in any dimension. The geometric model is a digital
surface with which an energy is associated. The model grows inside the
component to segment by following minimal energy paths. The
segmentation result is obtained a posteriori by examining the
energies of the successive model shapes. We validate our approach on
several 2D images.
Keywords: image segmentation, discrete deformable model, energy-minimization, digital surface
|
[3]
|
A. Vialard.
Simplification de contours pour la reconstruction surfacique.
Technical Report 1227-99, LaBRI, Talence, France, 1999.
[ bib ]
|
[4]
|
A. Vialard.
Chemins euclidiens : un modèle de représentation des contours
discrets.
PhD thesis, Université Bordeaux 1, France, 1996.
(en français).
[ bib ]
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