A fast persistence-based segmentation of noisy 2D clouds with provable guarantees

Kurlin, V ORCID: 0000-0001-5328-5351 (2016) A fast persistence-based segmentation of noisy 2D clouds with provable guarantees. Pattern Recognition Letters, 83 (1). pp. 3-12.

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Abstract

We design a new fast algorithm to automatically segment a 2D cloud of points into persistent regions. The only input is a dotted image without any extra parameters, say a scanned black-and-white map with almost closed curves or any image with detected edge points. The output is a hierarchy of segmentations into regions whose boundaries have a long enough life span (persistence) in a sequence of nested neighborhoods of the input points. We give conditions on a noisy sample of a graph, when the boundaries of resulting regions are geometrically close to original cycles in the unknown graph.

Item Type:	Article
Additional Information:	publisher: Elsevier articletitle: A fast persistence-based segmentation of noisy 2D clouds with provable guarantees journaltitle: Pattern Recognition Letters articlelink: http://dx.doi.org/10.1016/j.patrec.2015.11.025 content_type: article copyright: © 2015 Elsevier B.V. All rights reserved.
Uncontrolled Keywords:	Persistent homology, Delaunay triangulation, Cloud segmentation, Alpha complexes, Persistence diagram
Depositing User:	Symplectic Admin
Date Deposited:	14 Dec 2016 11:26
Last Modified:	19 Jan 2023 07:24
DOI:	10.1016/j.patrec.2015.11.025
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3004869