Automatic extraction and reconstruction of powerlines from airborne LiDAR point clouds

doi:10.13474/j.cnki.11-2246.2020.0313

Abstract

Abstract: In order to realize more effective inspection of powerline corridor, this paper designs a method for automatic extraction and reconstruction of powerline from LiDAR point cloud data. The improved progressive morphology filtering is used to eliminate the ground point. It achieves rough extraction of powerline points through the segmentation based on the height difference threshold and elevation dispersion. The powerline linear model is obtained through RANSAC line inspection, relying on density detection, precise clustering of single powerline points is achieved. It complete the bundled conductors classification with the k-means algorithm. Finally, a least square fitting of the quadratic polynomial is performed to generate a powerline curve model. Experiments show that the correct rate of powerline point cloud extraction is over 98%, the false positive rate of non-powerline point cloud is as low as 1%, the fitting error of powerline linear model is below 5 cm and the curve model is below 3 cm. Fully meet the actual engineering needs.

Key words: airborne LiDAR, powerline, extraction, reconstruction, precision analysis

CLC Number:

P237

ZHOU Qinkun, YUE Jianping, YANG Heng, ZHU Yimin. Automatic extraction and reconstruction of powerlines from airborne LiDAR point clouds[J]. Bulletin of Surveying and Mapping, 2020, 0(10): 26-30,37.

References

[1] 陈驰, 麦晓明, 宋爽, 等. 机载激光点云数据中电力线自动提取方法[J]. 武汉大学学报(信息科学版), 2015, 40(12):1600-1605.
[2] 徐博, 刘正军, 王坚. 基于激光点云数据电力线的提取及安全检测[J]. 激光杂志, 2017, 38(7):48-51.
[3] 王平华, 习晓环, 王成, 等. 机载激光雷达数据中电力线的快速提取[J]. 测绘科学, 2017, 42(2):154-158,171.
[4] 余洁, 穆超, 冯延明, 等. 机载LiDAR点云数据中电力线的提取方法研究[J]. 武汉大学学报(信息科学版), 2011, 36(11):1275-1279.
[5] 游安清, 潘旭东, 赵平, 等. 激光雷达电力巡线点云自动分类方法研究[J]. 应用光学, 2019, 40(6): 1077-1083.
[6] 叶岚, 刘倩, 胡庆武. 基于LiDAR点云数据的电力线提取和拟合方法研究[J]. 测绘与空间地理信息, 2010, 33(5): 30-34.
[7] 沈小军, 秦川, 杜勇, 等. 复杂地形电力线机载激光雷达点云自动提取方法[J]. 同济大学学报(自然科学版), 2018, 46(7): 982-987.
[8] 尹辉增, 孙轩, 聂振钢. 基于机载激光点云数据的电力线自动提取算法[J]. 地理与地理信息科学, 2012, 28(2): 31-34,2.
[9] 赵传, 张保明, 余东行, 等. 利用迁移学习的机载激光雷达点云分类[J]. 光学精密工程, 2019, 27(7): 1601-1612.
[10] 赖旭东, 戴大昌, 郑敏, 等. LiDAR点云数据的电力线3维重建[J]. 遥感学报, 2014, 18(6): 1223-1229.
[11] 林祥国, 张继贤. 架空输电线路机载激光雷达点云电力线三维重建[J]. 测绘学报, 2016, 45(3): 347-353.
[12] 张继贤, 段敏燕, 林祥国, 等. 激光雷达点云电力线三维重建模型的对比与分析[J]. 武汉大学学报(信息科学版), 2017, 42(11): 1565-1572.
[13] 林祥国, 段敏燕, 张继贤, 等. 一种机载LiDAR点云电力线三维重建方法[J]. 测绘科学, 2016, 41(1): 109-114,64.
[14] 杨渊, 陈凤翔, 虢韬, 等. 基于LiDAR点云特征和模型拟合的高压线提取[J]. 中国科学院大学学报, 2018, 35(5): 612-616.
[15] 麻卫峰, 王金亮, 王成, 等. 电力线点云精细提取与重建的模型残差实现[J]. 测绘科学, 2020, 45(2): 60-66.
[16] ZHANG Yongjun, XIONG Xiaodong, WANG Mengqiu, et al. A fast aerial image matching method using airborne LiDAR point cloud and POS data[J]. Journal of Geodesy and Geoinformation Science, 2019, 2(1): 26-36.