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A Novel Line Space Voting Method for Vanishing-Point Detection of General Road Images

Vanishing-point detection is an important component for the visual navigation system of an autonomous mobile robot. In this paper, we present a novel line space voting method for fast vanishing-point detection. First, the line segments are detected from the road image by the line segment detector (L...

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Detalles Bibliográficos
Autores principales: Wu, Zongsheng, Fu, Weiping, Xue, Ru, Wang, Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970002/
https://www.ncbi.nlm.nih.gov/pubmed/27347947
http://dx.doi.org/10.3390/s16070948
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author Wu, Zongsheng
Fu, Weiping
Xue, Ru
Wang, Wen
author_facet Wu, Zongsheng
Fu, Weiping
Xue, Ru
Wang, Wen
author_sort Wu, Zongsheng
collection PubMed
description Vanishing-point detection is an important component for the visual navigation system of an autonomous mobile robot. In this paper, we present a novel line space voting method for fast vanishing-point detection. First, the line segments are detected from the road image by the line segment detector (LSD) method according to the pixel’s gradient and texture orientation computed by the Sobel operator. Then, the vanishing-point of the road is voted on by considering the points of the lines and their neighborhood spaces with weighting methods. Our algorithm is simple, fast, and easy to implement with high accuracy. It has been experimentally tested with over hundreds of structured and unstructured road images. The experimental results indicate that the proposed method is effective and can meet the real-time requirements of navigation for autonomous mobile robots and unmanned ground vehicles.
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spelling pubmed-49700022016-08-04 A Novel Line Space Voting Method for Vanishing-Point Detection of General Road Images Wu, Zongsheng Fu, Weiping Xue, Ru Wang, Wen Sensors (Basel) Article Vanishing-point detection is an important component for the visual navigation system of an autonomous mobile robot. In this paper, we present a novel line space voting method for fast vanishing-point detection. First, the line segments are detected from the road image by the line segment detector (LSD) method according to the pixel’s gradient and texture orientation computed by the Sobel operator. Then, the vanishing-point of the road is voted on by considering the points of the lines and their neighborhood spaces with weighting methods. Our algorithm is simple, fast, and easy to implement with high accuracy. It has been experimentally tested with over hundreds of structured and unstructured road images. The experimental results indicate that the proposed method is effective and can meet the real-time requirements of navigation for autonomous mobile robots and unmanned ground vehicles. MDPI 2016-06-23 /pmc/articles/PMC4970002/ /pubmed/27347947 http://dx.doi.org/10.3390/s16070948 Text en © 2016 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
Wu, Zongsheng
Fu, Weiping
Xue, Ru
Wang, Wen
A Novel Line Space Voting Method for Vanishing-Point Detection of General Road Images
title A Novel Line Space Voting Method for Vanishing-Point Detection of General Road Images
title_full A Novel Line Space Voting Method for Vanishing-Point Detection of General Road Images
title_fullStr A Novel Line Space Voting Method for Vanishing-Point Detection of General Road Images
title_full_unstemmed A Novel Line Space Voting Method for Vanishing-Point Detection of General Road Images
title_short A Novel Line Space Voting Method for Vanishing-Point Detection of General Road Images
title_sort novel line space voting method for vanishing-point detection of general road images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970002/
https://www.ncbi.nlm.nih.gov/pubmed/27347947
http://dx.doi.org/10.3390/s16070948
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