当前位置: X-MOL 学术PFG J. Photogramm. Remote Sens. Geoinf. Sci. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A Robust and Efficient Method for Power Lines Extraction from Mobile LiDAR Point Clouds
PFG-Journal of Photogrammetry, Remote Sensing and Geoinformation Science ( IF 4.1 ) Pub Date : 2021-06-16 , DOI: 10.1007/s41064-021-00155-y
Danesh Shokri , Heidar Rastiveis , Wayne A. Sarasua , Alireza Shams , Saeid Homayouni

Monitoring, maintaining, and organizing power lines corridors are of great importance because they are a primary means to transfer generated electricity from power stations to surrounding areas. Mobile Terrestrial Laser Scanning (MTLS) systems have significant potential for efficiently creating a power line infrastructure inventory. In this paper, a novel algorithm is presented for automatically extracting utility poles and cables from MTLS point clouds in three consecutive phases of pre-processing, poles extraction, and cables extraction. In the pre-processing step, after dividing the MTLS data into several tiles or sections along the road and using trajectory data, noisy points and low-height points are eliminated from each section. Next, search areas containing lines are detected using a Hough Transform (HT) algorithm, and utility poles are identified based on horizontal and vertical density information. The search area for cables is estimated using a two-dimensional (2D) Delaunay Triangulation (DT) of the center points of the extracted poles as vertices. In each search area, high-density points are removed as non-cable points and utility cables are eventually extracted by fitting cable points to polynomial equations. The algorithm was tested on three different MTLS point clouds from a 1371 m urban road section, and a 2800 m and a 500 m non-urban road sections. Each of these datasets has unique challenges and was used to evaluate the efficiency of the proposed algorithm under different conditions. The algorithm was able to extract poles with average correctness of 100% (no false positives) and completeness of 97%. Similarly, average correctness and completeness of 100% and 95.6% were attained for cables, respectively. These detection levels show that the proposed method for power lines extraction from an MTLS point cloud is both reliable and feasible.



中文翻译:

从移动 LiDAR 点云中提取电力线的一种稳健有效的方法

监控、维护和组织电力线路走廊非常重要,因为它们是将发电量从发电站传输到周边地区的主要手段。移动地面激光扫描 (MTLS) 系统具有有效创建电力线基础设施清单的巨大潜力。在本文中,提出了一种新算法,用于在预处理、电线杆提取和电缆提取三个连续阶段中从 MTLS 点云中自动提取电线杆和电缆。在预处理步骤中,在将 MTLS 数据沿道路划分为若干个瓦片或部分后,利用轨迹数据,从每个部分中去除噪声点和低高度点。接下来,使用霍夫变换 (HT) 算法检测包含线条的搜索区域,根据水平和垂直密度信息识别电线杆。使用提取的极点中心点作为顶点的二维 (2D) Delaunay 三角剖分 (DT) 来估计电缆的搜索区域。在每个搜索区域中,作为非电缆点的高密度点被删除,最终通过将电缆点拟合到多项式方程来提取公用事业电缆。该算法在来自 1371 m 城市路段、2800 m 和 500 m 非城市路段的三种不同 MTLS 点云上进行了测试。这些数据集中的每一个都有独特的挑战,用于评估所提出算法在不同条件下的效率。该算法能够以 100% 的平均正确率(无误报)和 97% 的完整性提取极点。相似地,电缆的平均正确性和完整性分别达到 100% 和 95.6%。这些检测水平表明,所提出的从 MTLS 点云中提取电力线的方法既可靠又可行。

更新日期:2021-06-17
down
wechat
bug