Multi-band segmentation using morphological clustering and fusion application to color image segmentation

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Abstract

In this paper we propose a novel approach for color image segmentation. Our approach is based on segmentation of subsets of bands using mathematical morphology followed by the fusion of the resulting segmentation channels. For color images the band subsets are chosen as RG, RB and GB pairs, whose 2D histograms are processed as projections of a 3D histogram. The segmentations in 2D color spaces are obtained using the watershed algorithm. These 2D segmentations are then combined to obtain a final result using a region split-and-merge process. The CIE L a b color space is used to measure the color distance. Our approach results in improved performance and can be generalized for multi-band segmentation of images such as multi-spectral satellite images information.


Bibtex (lrde.bib)

@InProceedings{	  xue.03.icip,
  author	= {Heru Xue and Thierry G\'eraud and Alexandre Duret-Lutz},
  title		= {Multi-band segmentation using morphological clustering and
		  fusion application to color image segmentation},
  booktitle	= {Proceedings of the IEEE International Conference on Image
		  Processing (ICIP)},
  year		= 2003,
  pages		= {353--356},
  volume	= 1,
  address	= {Barcelona, Spain},
  month		= sep,
  abstract	= {In this paper we propose a novel approach for color image
		  segmentation. Our approach is based on segmentation of
		  subsets of bands using mathematical morphology followed by
		  the fusion of the resulting segmentation channels. For
		  color images the band subsets are chosen as RG, RB and GB
		  pairs, whose 2D histograms are processed as projections of
		  a 3D histogram. The segmentations in 2D color spaces are
		  obtained using the watershed algorithm. These 2D
		  segmentations are then combined to obtain a final result
		  using a region split-and-merge process. The CIE L a b color
		  space is used to measure the color distance. Our approach
		  results in improved performance and can be generalized for
		  multi-band segmentation of images such as multi-spectral
		  satellite images information.}
}