An Unsupervised Algorithm for Detecting Good Continuation in Dot Patterns

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Communicated by Julie Digne
Demo edited by José Lezama

Abstract

In this article we describe an algorithm for the automatic detection of perceptually relevant configurations of 'good continuation' of points in 2D point patterns. The algorithm is based on the 'a contrario' detection theory and on the assumption that 'good continuation' of points are locally quasi-symmetric. The algorithm has only one critical parameter, which controls the number of false detections.

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  Software Heritage Archive @softwareversion{sw-ipol.2017.176, title = {{An Unsupervised Algorithm for Detecting Good Continuation in Dot Patterns}}, author = {José Lezama, Gregory Randall, Jean-Michel Morel, Rafael Grompone von Gioi}, date = {2016-04-21}, license = {AGPL-3.0-or-later}, version = {0.4}, swhid = {swh:1:dir:e52c2f090c5c6ee8289756cc6b13f2d9836b7601;origin=https://doi.org/10.5201/ipol.2017.176;visit=swh:1:snp:ba055d8909147591e775ec6c8ffaaa19ef06f82f;anchor=swh:1:rel:d4fd331bcba2ab5f1d2645c8d6c4772c069e37db}, related = {ipol.2017.176}, relatedtype = "Reference article: https://doi.org/10.5201/ipol.2017.176" } % the biblatex-software style extension is recommended for software bibitems
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History

• Note from the editor: the manuscript of the article was modified on 2022-01-01 to include information about its editors. The original version of the manuscript is available here.