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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cloud2D-segmentation-full.pdf - Author Accepted Manuscript Download (4MB) |
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 |
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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: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3004869 |