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Bionic Vision-Based Intelligent Power Line Inspection System

Detecting the threats of the external obstacles to the power lines can ensure the stability of the power system. Inspired by the attention mechanism and binocular vision of human visual system, an intelligent power line inspection system is presented in this paper. Human visual attention mechanism i...

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Detalles Bibliográficos
Autores principales: Li, Qingwu, Ma, Yunpeng, He, Feijia, Xi, Shuya, Xu, Jinxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5288559/
https://www.ncbi.nlm.nih.gov/pubmed/28203269
http://dx.doi.org/10.1155/2017/4964287
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author Li, Qingwu
Ma, Yunpeng
He, Feijia
Xi, Shuya
Xu, Jinxin
author_facet Li, Qingwu
Ma, Yunpeng
He, Feijia
Xi, Shuya
Xu, Jinxin
author_sort Li, Qingwu
collection PubMed
description Detecting the threats of the external obstacles to the power lines can ensure the stability of the power system. Inspired by the attention mechanism and binocular vision of human visual system, an intelligent power line inspection system is presented in this paper. Human visual attention mechanism in this intelligent inspection system is used to detect and track power lines in image sequences according to the shape information of power lines, and the binocular visual model is used to calculate the 3D coordinate information of obstacles and power lines. In order to improve the real time and accuracy of the system, we propose a new matching strategy based on the traditional SURF algorithm. The experimental results show that the system is able to accurately locate the position of the obstacles around power lines automatically, and the designed power line inspection system is effective in complex backgrounds, and there are no missing detection instances under different conditions.
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spelling pubmed-52885592017-02-15 Bionic Vision-Based Intelligent Power Line Inspection System Li, Qingwu Ma, Yunpeng He, Feijia Xi, Shuya Xu, Jinxin Comput Math Methods Med Research Article Detecting the threats of the external obstacles to the power lines can ensure the stability of the power system. Inspired by the attention mechanism and binocular vision of human visual system, an intelligent power line inspection system is presented in this paper. Human visual attention mechanism in this intelligent inspection system is used to detect and track power lines in image sequences according to the shape information of power lines, and the binocular visual model is used to calculate the 3D coordinate information of obstacles and power lines. In order to improve the real time and accuracy of the system, we propose a new matching strategy based on the traditional SURF algorithm. The experimental results show that the system is able to accurately locate the position of the obstacles around power lines automatically, and the designed power line inspection system is effective in complex backgrounds, and there are no missing detection instances under different conditions. Hindawi Publishing Corporation 2017 2017-01-19 /pmc/articles/PMC5288559/ /pubmed/28203269 http://dx.doi.org/10.1155/2017/4964287 Text en Copyright © 2017 Qingwu Li et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Qingwu
Ma, Yunpeng
He, Feijia
Xi, Shuya
Xu, Jinxin
Bionic Vision-Based Intelligent Power Line Inspection System
title Bionic Vision-Based Intelligent Power Line Inspection System
title_full Bionic Vision-Based Intelligent Power Line Inspection System
title_fullStr Bionic Vision-Based Intelligent Power Line Inspection System
title_full_unstemmed Bionic Vision-Based Intelligent Power Line Inspection System
title_short Bionic Vision-Based Intelligent Power Line Inspection System
title_sort bionic vision-based intelligent power line inspection system
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5288559/
https://www.ncbi.nlm.nih.gov/pubmed/28203269
http://dx.doi.org/10.1155/2017/4964287
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AT xujinxin bionicvisionbasedintelligentpowerlineinspectionsystem