Morphological Filtering in Shape Spaces: Applications using Tree-Based Image Representations

Abstract : Connected operators are filtering tools that act by merging elementary regions of an image. A popular strategy is based 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 build from the image. Such a processing is a generalization of the existing tree-based connected operators. Indeed, the framework includes classical existing connected operators by attributes. It also allows us to propose a class of novel connected operators from the leveling family, based on shape attributes. Finally, we also propose a novel class of self-dual connected operators that we call morphological shapings.
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Contributor : Laurent Najman <>
Submitted on : Friday, November 30, 2012 - 5:34:45 PM
Last modification on : Thursday, July 5, 2018 - 2:25:26 PM

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  • HAL Id : hal-00714847, version 1
  • ARXIV : 1204.4758

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Yongchao Xu, Thierry Géraud, Laurent Najman. Morphological Filtering in Shape Spaces: Applications using Tree-Based Image Representations. 21st International Conference on Pattern Recognition, Nov 2012, Tsukuba, Japan. pp.485-488. ⟨hal-00714847⟩

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