Segmentation d'images en couleur par classification morphologique non supervisée

From LRDE

Revision as of 17:57, 4 January 2018 by Bot (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

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},
  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.}
}