Difference between revisions of "Publications/geraud.03.ibpria"
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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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| type = inproceedings |
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| id = geraud.03.ibpria |
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our framework are numerous: they go from simple surve |
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segmentation to complex road network extraction in |
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Revision as of 18:07, 4 November 2013
- Authors
- Thierry Géraud
- Where
- Proceedings of the 1st Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)
- Place
- Mallorca, Spain
- Type
- inproceedings
- Publisher
- Springer-Verlag
- 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.ibpria,
author = {Thierry G\'eraud},
title = {Segmentation of curvilinear objects using a
watershed-based curve adjacency graph},
booktitle = {Proceedings of the 1st Iberian Conference on Pattern
Recognition and Image Analysis (IbPRIA)},
pages = {279--286},
year = 2003,
editor = {Springer-Verlag},
volume = 2652,
series = {Lecture Notes in Computer Science Series},
address = {Mallorca, Spain},
month = jun,
publisher = {Springer-Verlag},
project = {Image},
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.},
lrdekeywords = {Image}
}