Reconstructing persistent graph structures from noisy images

Chernov, Alexey; Kurlin, Vitaliy

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.

Citation

Chernov, A., & Kurlin, V. (2013). Reconstructing persistent graph structures from noisy images. Imagen-a, 3(5), 19-22

• Journal Article Type: Article
• Publication Date: Jan 1, 2013
• Deposit Date: Nov 15, 2013
• Publicly Available Date: Feb 18, 2014
• Journal: Image-a. = Imagen-a
• Electronic ISSN: 1885-4508
• Publisher: Publishing House of the University of Seville
• Peer Reviewed: Peer Reviewed
• Volume: 3
• Issue: 5
• Article Number: 5.3
• Pages: 19-22
• Keywords: Graph reconstruction, Noisy image, Point cloud data, Persistent topology.
• Public URL: https://durham-repository.worktribe.com/output/1474902
• Publisher URL: http://munkres.us.es/Volume3/Volumen3/N_5.html