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A Robust Method for Detecting Parking Areas in Both Indoor and Outdoor Environments

Although an automatic parking system has been installed in many vehicles recently, it is still hard for the system to confirm by itself whether a vacant parking area truly exists or not. In this paper, we introduced a robust vision-based vacancy parking area detecting method for both indoor and outd...

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Detalles Bibliográficos
Autores principales: Zong, Wenhao, Chen, Qijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022088/
https://www.ncbi.nlm.nih.gov/pubmed/29891826
http://dx.doi.org/10.3390/s18061903
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author Zong, Wenhao
Chen, Qijun
author_facet Zong, Wenhao
Chen, Qijun
author_sort Zong, Wenhao
collection PubMed
description Although an automatic parking system has been installed in many vehicles recently, it is still hard for the system to confirm by itself whether a vacant parking area truly exists or not. In this paper, we introduced a robust vision-based vacancy parking area detecting method for both indoor and outdoor environments. The main contribution of this paper is given as follows. First, an automatic image stitching method is proposed. Secondly, the problem of environment illuminating change and line color difference is considered and solved. Thirdly, the proposed algorithm is insensitive to the shadow and scene diversity, which means the detecting result satisfies most of the environment. Finally, a vehicle model is considered for tracking and reconfirming the detecting results to eliminate most of the false positives.
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spelling pubmed-60220882018-07-02 A Robust Method for Detecting Parking Areas in Both Indoor and Outdoor Environments Zong, Wenhao Chen, Qijun Sensors (Basel) Article Although an automatic parking system has been installed in many vehicles recently, it is still hard for the system to confirm by itself whether a vacant parking area truly exists or not. In this paper, we introduced a robust vision-based vacancy parking area detecting method for both indoor and outdoor environments. The main contribution of this paper is given as follows. First, an automatic image stitching method is proposed. Secondly, the problem of environment illuminating change and line color difference is considered and solved. Thirdly, the proposed algorithm is insensitive to the shadow and scene diversity, which means the detecting result satisfies most of the environment. Finally, a vehicle model is considered for tracking and reconfirming the detecting results to eliminate most of the false positives. MDPI 2018-06-11 /pmc/articles/PMC6022088/ /pubmed/29891826 http://dx.doi.org/10.3390/s18061903 Text en © 2018 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
Zong, Wenhao
Chen, Qijun
A Robust Method for Detecting Parking Areas in Both Indoor and Outdoor Environments
title A Robust Method for Detecting Parking Areas in Both Indoor and Outdoor Environments
title_full A Robust Method for Detecting Parking Areas in Both Indoor and Outdoor Environments
title_fullStr A Robust Method for Detecting Parking Areas in Both Indoor and Outdoor Environments
title_full_unstemmed A Robust Method for Detecting Parking Areas in Both Indoor and Outdoor Environments
title_short A Robust Method for Detecting Parking Areas in Both Indoor and Outdoor Environments
title_sort robust method for detecting parking areas in both indoor and outdoor environments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022088/
https://www.ncbi.nlm.nih.gov/pubmed/29891826
http://dx.doi.org/10.3390/s18061903
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