Reconstructing persistent graph structures from noisy images

Alexey Chernov, Vitaliy Kurlin

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Let a point cloud be a noisy dotted image of a graph on the plane. We present a new fast algorithm for reconstructing the original graph from the given point cloud. Degrees of vertices in the graph are found by methods of persistent topology. Necessary parameters are automatically optimized by machine learning tools.
Original languageEnglish
Pages (from-to)19-22
Number of pages4
JournalImage-A: Applicable Mathematics in Image Engineering
Volume3
Issue number5
Publication statusPublished - 15 Mar 2013

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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 International License

Cite this

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Reconstructing persistent graph structures from noisy images. / Chernov, Alexey; Kurlin, Vitaliy.

In: Image-A: Applicable Mathematics in Image Engineering, Vol. 3, No. 5, 15.03.2013, p. 19-22.

Research output: Contribution to journalArticleResearchpeer-review

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