Meaningful disjoint level lines selection

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Abstract

Many methods based on the morphological notion of shapes (textiti.e., connected components of level sets) have been proved to be very efficient in shape recognition and shape analysis. The inclusion relationship of the level lines (boundaries of level sets) forms the tree of shapes, a tree-based image representation with a high potential. Numerous applications using this tree representation have been proposed. In this article, we propose an efficient algorithm that extracts a set of disjoint level lines in the image. These selected level lines yields a simplified image with clean contours, which also provides an intuitive idea about the main structure of the tree of shapes. Besides, we obtain a saliency map without transition problems around the contours by weighting level lines with their significance. Experimental results demonstrate the efficiency and usefulness of our method.

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Bibtex (lrde.bib)

@InProceedings{	  xu.14.icip,
  author	= {Yongchao Xu and Edwin Carlinet and Thierry G\'eraud and
		  Laurent Najman},
  title		= {Meaningful disjoint level lines selection},
  booktitle	= {Proceedings of the 21st International Conference on Image
		  Processing (ICIP)},
  year		= 2014,
  address	= {Paris, France},
  pages		= {2938--2942},
  abstract	= {Many methods based on the morphological notion of
		  \textit{shapes} (\textit{i.e.}, connected components of
		  level sets) have been proved to be very efficient in shape
		  recognition and shape analysis. The inclusion relationship
		  of the level lines (boundaries of level sets) forms the
		  tree of shapes, a tree-based image representation with a
		  high potential. Numerous applications using this tree
		  representation have been proposed. In this article, we
		  propose an efficient algorithm that extracts a set of
		  disjoint level lines in the image. These selected level
		  lines yields a simplified image with clean contours, which
		  also provides an intuitive idea about the main structure of
		  the tree of shapes. Besides, we obtain a saliency map
		  without transition problems around the contours by
		  weighting level lines with their significance. Experimental
		  results demonstrate the efficiency and usefulness of our
		  method. }
}