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Particle Swarm Contour Search Algorithm

In this article, we present a new algorithm called Particle Swarm Contour Search (PSCS)—a Particle Swarm Optimisation inspired algorithm to find object contours in 2D environments. Currently, most contour-finding algorithms are based on image processing and require a complete overview of the search...

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Detalles Bibliográficos
Autores principales: Weikert, Dominik, Mai, Sebastian, Mostaghim, Sanaz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516883/
https://www.ncbi.nlm.nih.gov/pubmed/33286181
http://dx.doi.org/10.3390/e22040407
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author Weikert, Dominik
Mai, Sebastian
Mostaghim, Sanaz
author_facet Weikert, Dominik
Mai, Sebastian
Mostaghim, Sanaz
author_sort Weikert, Dominik
collection PubMed
description In this article, we present a new algorithm called Particle Swarm Contour Search (PSCS)—a Particle Swarm Optimisation inspired algorithm to find object contours in 2D environments. Currently, most contour-finding algorithms are based on image processing and require a complete overview of the search space in which the contour is to be found. However, for real-world applications this would require a complete knowledge about the search space, which may not be always feasible or possible. The proposed algorithm removes this requirement and is only based on the local information of the particles to accurately identify a contour. Particles search for the contour of an object and then traverse alongside using their known information about positions in- and out-side of the object. Our experiments show that the proposed PSCS algorithm can deliver comparable results as the state-of-the-art.
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spelling pubmed-75168832020-11-09 Particle Swarm Contour Search Algorithm Weikert, Dominik Mai, Sebastian Mostaghim, Sanaz Entropy (Basel) Article In this article, we present a new algorithm called Particle Swarm Contour Search (PSCS)—a Particle Swarm Optimisation inspired algorithm to find object contours in 2D environments. Currently, most contour-finding algorithms are based on image processing and require a complete overview of the search space in which the contour is to be found. However, for real-world applications this would require a complete knowledge about the search space, which may not be always feasible or possible. The proposed algorithm removes this requirement and is only based on the local information of the particles to accurately identify a contour. Particles search for the contour of an object and then traverse alongside using their known information about positions in- and out-side of the object. Our experiments show that the proposed PSCS algorithm can deliver comparable results as the state-of-the-art. MDPI 2020-04-02 /pmc/articles/PMC7516883/ /pubmed/33286181 http://dx.doi.org/10.3390/e22040407 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Weikert, Dominik
Mai, Sebastian
Mostaghim, Sanaz
Particle Swarm Contour Search Algorithm
title Particle Swarm Contour Search Algorithm
title_full Particle Swarm Contour Search Algorithm
title_fullStr Particle Swarm Contour Search Algorithm
title_full_unstemmed Particle Swarm Contour Search Algorithm
title_short Particle Swarm Contour Search Algorithm
title_sort particle swarm contour search algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516883/
https://www.ncbi.nlm.nih.gov/pubmed/33286181
http://dx.doi.org/10.3390/e22040407
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