2026-06-02T21:33:47Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/292192026-02-03T11:19:30Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Thurnhofer-Hemsi, Karl
author
López-Rubio, Ezequiel
author
Blázquez-Parra, Elidia Beatriz
author
Ladrón-de-Guevara-Muñoz, María del Carmen
author
De-Cózar-Macías, Óscar
2024-01-25T12:30:02Z
2024-01-25T12:30:02Z
2020-05
https://hdl.handle.net/10630/29219
10.1016/j.patcog.2020.107406
Earlier ellipse fitting methods often consider the algebraic and geometric forms of the ellipse. The work presented here makes use of an ensemble to provide better results. The method proposes a new ellipse parametrization based on the coordinates of both foci, and the distance between them and each point of the ellipse where the Euclidean norm is applied. Besides, a certain number of subsets are uniformly drawn without replacement from the overall training set which allows estimating the center of the distribution robustly by employing the L1 median of each estimated focus. An additional postprocessing stage is proposed to filter out the effect of bad fits. In order to evaluate the performance of this method, four different error measures were considered. Results show that our proposal outperforms all its competitors, especially when higher levels of outliers are presented. Several synthetic and real data tests were developed and confirmed such finding.
eng
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Curvas
Geometría
Curvas elípticas
Curvas algebraicas
Ellipse fitting by spatial averaging of random ensembles
journal article
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URL
https://riuma.uma.es/bitstreams/71a9aac5-615d-41e4-9d84-b168cd3fcfcb/download
File
MD5
3fda1fa30844332c4d12143fc52b86b8
16432363
application/pdf
ViewPageProof_PR_107406.pdf