Publications/xu.13.ismm

Authors

Yongchao Xu, Thierry Géraud, Laurent Najman

Where

Mathematical Morphology and Its Application to Signal and Image Processing -- Proceedings of the 11th International Symposium on Mathematical Morphology (ISMM)

Place

Heidelberg

Type

inproceedings

Publisher

Springer

Keywords

Image

Date

2013-03-14

Abstract

Connected filtering is a popular strategy that relies on tree- based image representations: for example, one can compute an attribute on each node of the tree and keep only the nodes for which the attribute is sufficiently strong. This operation can be seen as a thresholding of the treeseen as a graph whose nodes are weighted by the attribute. Rather than being satisfied with a mere thresholding, we propose to expand on this idea, and to apply connected filters on this latest graph. Consequently, the filtering is done not in the space of the image, but on the space of shapes built from the image. Such a processing, that we called shape-based morphology, is a generalization of the existing tree-based connected operators. In this paper, two different applications are studied: in the first one, we apply our framework to blood vessels segmentation in retinal images. In the second one, we propose an extension of constrained connectivity. In both cases, quantitative evaluations demonstrate that shape-based filtering, a mere filtering step that we compare to more evolved processingsachieves state-of-the-art results.

Documents

• Paper

Bibtex (lrde.bib)

@InProceedings{	  xu.13.ismm,
  author	= {Yongchao Xu and Thierry G\'eraud and Laurent Najman},
  title		= {Two applications of shape-based morphology: blood vessels
		  segmentation and a generalization of constrained
		  connectivity},
  booktitle	= {Mathematical Morphology and Its Application to Signal and
		  Image Processing -- Proceedings of the 11th International
		  Symposium on Mathematical Morphology (ISMM)},
  year		= 2013,
  editor	= {C.L. Luengo Hendriks and G. Borgefors and R. Strand},
  volume	= 7883,
  series	= {Lecture Notes in Computer Science Series},
  address	= {Heidelberg},
  publisher	= {Springer},
  pages		= {390--401},
  project	= {Image},
  abstract	= {Connected filtering is a popular strategy that relies on
		  tree- based image representations: for example, one can
		  compute an attribute on each node of the tree and keep only
		  the nodes for which the attribute is sufficiently strong.
		  This operation can be seen as a thresholding of the tree,
		  seen as a graph whose nodes are weighted by the attribute.
		  Rather than being satisfied with a mere thresholding, we
		  propose to expand on this idea, and to apply connected
		  filters on this latest graph. Consequently, the filtering
		  is done not in the space of the image, but on the space of
		  shapes built from the image. Such a processing, that we
		  called shape-based morphology, is a generalization of the
		  existing tree-based connected operators. In this paper, two
		  different applications are studied: in the first one, we
		  apply our framework to blood vessels segmentation in
		  retinal images. In the second one, we propose an extension
		  of constrained connectivity. In both cases, quantitative
		  evaluations demonstrate that shape-based filtering, a mere
		  filtering step that we compare to more evolved processings,
		  achieves state-of-the-art results.}
}