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Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12008/8904 How cite
Title: An unsupervised algorithm for detecting good continuation in Dot Patterns
Authors: Lezama, José
Randall, Gregory
Morel, Jean-Michel
Grompone von Gioi, Rafael
Type: Artículo
Keywords: Good continuation, Gestalt, Dots, Non-accidentalness, Local symmetry
Issue Date: 2017
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.
Publisher: Udelar. FI-IIE
IN: IPOL. Journal Image Processing On Line, 2017, vol. 7, pp. 81--92
ISSN: 2105-1232
Citation: LEZAMA, José, RANDALL, Gregory, MOREL, Jean-Michel, y otros. "An unsupervised algorithm for detecting good continuation in Dot Patterns". IPOL. Journal Image Processing On Line. [en línea] 2017, vol. 7, pp. 81--92.
License: Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC BY-NC-SA 4.0)
Appears in Collections:Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica

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