基于LIDAR点云数据的电力线提取和拟合方法研究

Research of Power Line Fitting and Extraction Techniques Based on LIDAR Point Cloud Data

从LIDAR电力线扫描数据的高程分布特点出发,提出了基于点云高程数据平面投影的电力线提取和拟合算法。首先通过高程自动阈值分割初步剔除地面点;其次,通过高程投影和重采样将高程分布转换为高程值影像,在影像空间通过直线检测实现电力线提取和拟合;最后,提出了基于数学形态学的电塔分割和潜在危险地物检测。通过对LIDAR点云数据电力线提取和拟合试验表明,本文算法能较好地实现电力线拟合、电塔提取及危险地物检测,可用于基于LIDAR的电力巡线。

According to the characteristic of elevation distribution,a power line extraction and fitting algorithm based on plane projection of point cloud elevation data is proposed in this paper.Firstly,an automatic elevation threshold segmentation method is presented to reject the terrestrial points primarily from the point cloud data.Secondly,an elevation project and resample algorithm is adopted to convert cloud point data to elevation-value-image.Power line extraction and filtering are implemented in the elevation-value image with line extraction algorithm in image domain.Finally,an electric-tower segmentation and potential dangerous ground objects detection technique based on mathematical morphology is proposed.The experiment result shows the algorithm can achieve power line fitting,electric-tower extraction and potential dangerous ground objects detection to the point cloud data and it can be used in power line inspection project based on LIDAR technique.