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Conference Papers Year : 2023

Hausdorff and Gromov-Hausdorff Stable Subsets of the Medial Axis

Abstract

In this paper we introduce a pruning of the medial axis called the (λ,α)-medial axis (axαλ). We prove that the (λ,α)-medial axis of a set K is stable in a Gromov-Hausdorff sense under weak assumptions. More formally we prove that if K and K′ are close in the Hausdorff (dH) sense then the (λ,α)-medial axes of K and K′ are close as metric spaces, that is the Gromov-Hausdorff distance (dGH) between the two is 14-H{ö}lder in the sense that dGH(axαλ(K),axαλ(K′))≲dH(K,K′)1/4. The Hausdorff distance between the two medial axes is also bounded, by dH(axαλ(K),axαλ(K′))≲dH(K,K′)1/2. These quantified stability results provide guarantees for practical computations of medial axes from approximations. Moreover, they provide key ingredients for studying the computability of the medial axis in the context of computable analysis.
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Dates and versions

hal-04095824 , version 1 (12-05-2023)

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André Lieutier, Mathijs Wintraecken. Hausdorff and Gromov-Hausdorff Stable Subsets of the Medial Axis. STOC 2023 - 55th Annual ACM Symposium on Theory of Computing, ACM, Jun 2023, Orlando (Florida), United States. pp.1768-1776, ⟨10.1145/3564246.3585113⟩. ⟨hal-04095824⟩
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