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Article Dans Une Revue Journal of Mathematical Imaging and Vision Année : 2024

Assessing hierarchies by their consistent segmentations

Résumé

Current approaches to generic segmentation start by creating a hierarchy of nested image partitions and then specifying a segmentation from it. Our first contribution is to describe several ways, most of them new, for specifying segmentations using the hierarchy elements. Then, we consider the best hierarchy-induced segmentation specified by a limited number of hierarchy elements. We focus on a common quality measure for binary segmentations, the Jaccard index (also known as IoU). Optimizing the Jaccard index is highly non-trivial, and yet we propose an efficient approach for doing exactly that. This way we get algorithm-independent upper bounds on the quality of any segmentation created from the hierarchy. We found that the obtainable segmentation quality varies significantly depending on the way that the segments are specified by the hierarchy elements, and that representing a segmentation with only a few hierarchy elements is often possible. (Code is available).
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Dates et versions

hal-03633805 , version 1 (08-04-2022)
hal-03633805 , version 2 (06-12-2023)

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Zeev Gutman, Ritvik Vij, Laurent Najman, Michael Lindenbaum. Assessing hierarchies by their consistent segmentations. Journal of Mathematical Imaging and Vision, 2024, ⟨10.1007/s10851-024-01176-z⟩. ⟨hal-03633805v2⟩
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