Difference between revisions of "Publications/geraud.01.icisp"
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| abstract = In this paper, we present an original method to segment color images using a classification of the image histogram in the 3D color space. As color modes in natural images usually do not fit a well-known statistical model, we propose a classifier that rely on mathematical morphology and, more particularly, on the watershed algorithm. We show on various images that the expected color modes are correctly identified and, in order to obtain coherent region, we extend the method to make the segmentation contextual. |
| abstract = In this paper, we present an original method to segment color images using a classification of the image histogram in the 3D color space. As color modes in natural images usually do not fit a well-known statistical model, we propose a classifier that rely on mathematical morphology and, more particularly, on the watershed algorithm. We show on various images that the expected color modes are correctly identified and, in order to obtain coherent region, we extend the method to make the segmentation contextual. |
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+ | | lrdepaper = http://www.lrde.epita.fr/dload/papers/icisp01.pdf |
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+ | | lrdekeywords = Image |
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| type = inproceedings |
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Revision as of 18:07, 4 November 2013
- Authors
- Thierry Géraud, Pierre-Yves Strub, Jérôme Darbon
- 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
- Keywords
- Image
- Date
- 2001-05-01
Abstract
In this paper, we present an original method to segment color images using a classification of the image histogram in the 3D color space. As color modes in natural images usually do not fit a well-known statistical model, we propose a classifier that rely on mathematical morphology and, more particularly, on the watershed algorithm. We show on various images that the expected color modes are correctly identified and, in order to obtain coherent region, we extend the method to make the segmentation contextual.
Documents
Bibtex (lrde.bib)
@InProceedings{ geraud.01.icisp, author = {Thierry G\'eraud and Pierre-Yves Strub and J\'er\^ome Darbon}, title = {Segmentation d'images en couleur par classification morphologique non supervis\'ee}, booktitle = {Proceedings of the International Conference on Image and Signal Processing (ICISP)}, year = 2001, pages = {387--394}, address = {Agadir, Morocco}, month = may, publisher = {Faculty of Sciences at Ibn Zohr University, Morocco}, note = {In French}, project = {Image}, abstract = {In this paper, we present an original method to segment color images using a classification of the image histogram in the 3D color space. As color modes in natural images usually do not fit a well-known statistical model, we propose a classifier that rely on mathematical morphology and, more particularly, on the watershed algorithm. We show on various images that the expected color modes are correctly identified and, in order to obtain coherent region, we extend the method to make the segmentation contextual.}, lrdekeywords = {Image} }