Difference between revisions of "Publications/geraud.03.icisp"
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{{Publication |
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| date = 2003-06-01 |
| date = 2003-06-01 |
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| authors = Thierry Géraud |
| authors = Thierry Géraud |
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| publisher = Faculty of Sciences at Ibn Zohr University, Morocco |
| publisher = Faculty of Sciences at Ibn Zohr University, Morocco |
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| note = In French |
| note = In French |
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| abstract = This paper presents a general framework to segment curvilinear objects in 2D images. A pre-processing step relies on mathematical morphology to obtain a connected line which encloses curvilinear objects. Then, a graph is constructed from this line and a Markovian Random Field is defined to perform objects segmentation. Applications of our framework are numerous: they go from simple surve segmentation to complex road network extraction in satellite images. |
| abstract = This paper presents a general framework to segment curvilinear objects in 2D images. A pre-processing step relies on mathematical morphology to obtain a connected line which encloses curvilinear objects. Then, a graph is constructed from this line and a Markovian Random Field is defined to perform objects segmentation. Applications of our framework are numerous: they go from simple surve segmentation to complex road network extraction in satellite images. |
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| lrdekeywords = Image |
| lrdekeywords = Image |
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publisher = <nowiki>{</nowiki>Faculty of Sciences at Ibn Zohr University, Morocco<nowiki>}</nowiki>, |
publisher = <nowiki>{</nowiki>Faculty of Sciences at Ibn Zohr University, Morocco<nowiki>}</nowiki>, |
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note = <nowiki>{</nowiki>In French<nowiki>}</nowiki>, |
note = <nowiki>{</nowiki>In French<nowiki>}</nowiki>, |
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| − | project = <nowiki>{</nowiki>Image<nowiki>}</nowiki>, |
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abstract = <nowiki>{</nowiki>This paper presents a general framework to segment |
abstract = <nowiki>{</nowiki>This paper presents a general framework to segment |
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curvilinear objects in 2D images. A pre-processing step |
curvilinear objects in 2D images. A pre-processing step |
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our framework are numerous: they go from simple surve |
our framework are numerous: they go from simple surve |
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segmentation to complex road network extraction in |
segmentation to complex road network extraction in |
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| − | satellite images.<nowiki>}</nowiki> |
+ | satellite images.<nowiki>}</nowiki> |
| − | lrdekeywords = <nowiki>{</nowiki>Image<nowiki>}</nowiki> |
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<nowiki>}</nowiki> |
<nowiki>}</nowiki> |
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Latest revision as of 18:57, 4 January 2018
- Authors
- Thierry Géraud
- Where
- Proceedings of the International Conference on Image and Signal Processing (ICISP)
- Place
- Agadir, Morocco
- Type
- inproceedings
- Publisher
- Faculty of Sciences at Ibn Zohr University, Morocco
- Projects
- Olena
- Keywords
- Image
- Date
- 2003-06-01
Abstract
This paper presents a general framework to segment curvilinear objects in 2D images. A pre-processing step relies on mathematical morphology to obtain a connected line which encloses curvilinear objects. Then, a graph is constructed from this line and a Markovian Random Field is defined to perform objects segmentation. Applications of our framework are numerous: they go from simple surve segmentation to complex road network extraction in satellite images.
Bibtex (lrde.bib)
@InProceedings{ geraud.03.icisp,
author = {Thierry G\'eraud},
title = {Segmentation d'objets curvilignes \`a l'aide des champs de
Markov sur un graphe d'adjacence de courbes issu de
l'algorithme de la ligne de partage des eaux},
booktitle = {Proceedings of the International Conference on Image and
Signal Processing (ICISP)},
year = 2003,
volume = 2,
pages = {404--411},
address = {Agadir, Morocco},
month = jun,
publisher = {Faculty of Sciences at Ibn Zohr University, Morocco},
note = {In French},
abstract = {This paper presents a general framework to segment
curvilinear objects in 2D images. A pre-processing step
relies on mathematical morphology to obtain a connected
line which encloses curvilinear objects. Then, a graph is
constructed from this line and a Markovian Random Field is
defined to perform objects segmentation. Applications of
our framework are numerous: they go from simple surve
segmentation to complex road network extraction in
satellite images.}
}