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Combinatorial space of watershed hierarchies for image characterization

Abstract : We propose a framework for image characterization using hierarchies of segmentations. For this purpose, we structure the space of hierarchies using the Gromov–Hausdorff distance. We propose different ways of combining hierarchies and study their properties thanks to the GH distance. We then expose how to leverage the combinatorial space of hierarchies to derive efficient image representations. This framework opens a path for a controlled exploration and use of the combinatorial space of hierarchies.
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Contributor : Santiago Velasco-Forero Connect in order to contact the contributor
Submitted on : Tuesday, January 7, 2020 - 11:39:45 AM
Last modification on : Wednesday, November 17, 2021 - 12:27:17 PM

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Amin Fehri, Santiago Velasco-Forero, Fernand Meyer. Combinatorial space of watershed hierarchies for image characterization. Pattern Recognition Letters, Elsevier, 2020, 129, pp.41-47. ⟨10.1016/j.patrec.2019.11.002⟩. ⟨hal-02430341⟩



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