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https://hdl.handle.net/20.500.12008/8904
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| 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 |
Files in This Item:
| File | Description | Size | Format | ||
|---|---|---|---|---|---|
| LRMG17.pdf | 1,26 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License
