Cargando…

Customized Mobile LiDAR System for Manhole Cover Detection and Identification

Manhole covers, which are a key element of urban infrastructure management, have a direct impact on travel safety. At present, there is no automatic, safe, and efficient system specially used for the intelligent detection, identification, and assessment of manhole covers. In this work, we developed...

Descripción completa

Detalles Bibliográficos
Autores principales: Wei, Zhanying, Yang, Mengmeng, Wang, Liuzhao, Ma, Hao, Chen, Xuexia, Zhong, Ruofei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6566314/
https://www.ncbi.nlm.nih.gov/pubmed/31137919
http://dx.doi.org/10.3390/s19102422
_version_ 1783426825680060416
author Wei, Zhanying
Yang, Mengmeng
Wang, Liuzhao
Ma, Hao
Chen, Xuexia
Zhong, Ruofei
author_facet Wei, Zhanying
Yang, Mengmeng
Wang, Liuzhao
Ma, Hao
Chen, Xuexia
Zhong, Ruofei
author_sort Wei, Zhanying
collection PubMed
description Manhole covers, which are a key element of urban infrastructure management, have a direct impact on travel safety. At present, there is no automatic, safe, and efficient system specially used for the intelligent detection, identification, and assessment of manhole covers. In this work, we developed an automatic detection, identification, and assessment system for manhole covers. First, we developed a sequential exposure system via the addition of multiple cameras in a symmetrical arrangement to realize the joint acquisition of high-precision laser data and ultra-high-resolution ground images. Second, we proposed an improved histogram of an oriented gradient with symmetry features and a support vector machine method to detect manhole covers effectively and accurately, by using the intensity images and ground orthophotos that are derived from the laser points and images, respectively, and apply the graph segmentation and statistical analysis to achieve the detection, identification, and assessment of manhole covers. Qualitative and quantitative analyses are performed using large experimental datasets that were acquired with the modified manhole-cover detection system. The detected results yield an average accuracy of 96.18%, completeness of 94.27%, and F-measure value of 95.22% in manhole cover detection. Defective manhole-cover monitoring and manhole-cover ownership information are achieved from these detection results. The results not only provide strong support for road administration works, such as data acquisition, manhole cover inquiry and inspection, and statistical analysis of resources, but also demonstrate the feasibility and effectiveness of the proposed method, which reduces the risk involved in performing manual inspections, improves the manhole-cover detection accuracy, and serves as a powerful tool in intelligent road administration.
format Online
Article
Text
id pubmed-6566314
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-65663142019-06-17 Customized Mobile LiDAR System for Manhole Cover Detection and Identification Wei, Zhanying Yang, Mengmeng Wang, Liuzhao Ma, Hao Chen, Xuexia Zhong, Ruofei Sensors (Basel) Article Manhole covers, which are a key element of urban infrastructure management, have a direct impact on travel safety. At present, there is no automatic, safe, and efficient system specially used for the intelligent detection, identification, and assessment of manhole covers. In this work, we developed an automatic detection, identification, and assessment system for manhole covers. First, we developed a sequential exposure system via the addition of multiple cameras in a symmetrical arrangement to realize the joint acquisition of high-precision laser data and ultra-high-resolution ground images. Second, we proposed an improved histogram of an oriented gradient with symmetry features and a support vector machine method to detect manhole covers effectively and accurately, by using the intensity images and ground orthophotos that are derived from the laser points and images, respectively, and apply the graph segmentation and statistical analysis to achieve the detection, identification, and assessment of manhole covers. Qualitative and quantitative analyses are performed using large experimental datasets that were acquired with the modified manhole-cover detection system. The detected results yield an average accuracy of 96.18%, completeness of 94.27%, and F-measure value of 95.22% in manhole cover detection. Defective manhole-cover monitoring and manhole-cover ownership information are achieved from these detection results. The results not only provide strong support for road administration works, such as data acquisition, manhole cover inquiry and inspection, and statistical analysis of resources, but also demonstrate the feasibility and effectiveness of the proposed method, which reduces the risk involved in performing manual inspections, improves the manhole-cover detection accuracy, and serves as a powerful tool in intelligent road administration. MDPI 2019-05-27 /pmc/articles/PMC6566314/ /pubmed/31137919 http://dx.doi.org/10.3390/s19102422 Text en © 2019 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
Wei, Zhanying
Yang, Mengmeng
Wang, Liuzhao
Ma, Hao
Chen, Xuexia
Zhong, Ruofei
Customized Mobile LiDAR System for Manhole Cover Detection and Identification
title Customized Mobile LiDAR System for Manhole Cover Detection and Identification
title_full Customized Mobile LiDAR System for Manhole Cover Detection and Identification
title_fullStr Customized Mobile LiDAR System for Manhole Cover Detection and Identification
title_full_unstemmed Customized Mobile LiDAR System for Manhole Cover Detection and Identification
title_short Customized Mobile LiDAR System for Manhole Cover Detection and Identification
title_sort customized mobile lidar system for manhole cover detection and identification
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6566314/
https://www.ncbi.nlm.nih.gov/pubmed/31137919
http://dx.doi.org/10.3390/s19102422
work_keys_str_mv AT weizhanying customizedmobilelidarsystemformanholecoverdetectionandidentification
AT yangmengmeng customizedmobilelidarsystemformanholecoverdetectionandidentification
AT wangliuzhao customizedmobilelidarsystemformanholecoverdetectionandidentification
AT mahao customizedmobilelidarsystemformanholecoverdetectionandidentification
AT chenxuexia customizedmobilelidarsystemformanholecoverdetectionandidentification
AT zhongruofei customizedmobilelidarsystemformanholecoverdetectionandidentification