3D model reconstruction method for airborne radar power lines based on geometric features
This paper introduced an automatic extraction and reconstruction method for power lines based on laser point clouds.Firstly,the point clouds were filtered to provide a clearer data foundation for subsequent processing.Secondly,a set of geometric feature evaluation methods was developed,which assigned normalized evaluation scores to each feature by constructing feature vectors and assessing the significance of each feature.By setting reasonable score thresholds,a candidate point set for power lines was extracted.Finally,the power lines were successfully extracted by using a dual K-means algorithm.Tests using laser point cloud data have shown that this method achieves remarkable results in power line extraction,with both recall and precision rates exceeding 97%.This fully demonstrates the method's efficient and accurate extraction and reconstruction capabilities for power lines.This method injects new vitality into the development of automatic extraction and reconstruction of power line point clouds and provides technical support for practical engineering applications.
airborne light detection and ranging(LiDAR)power line extractionprogressive triangulation filteringfeature evaluationdual K-means algorithm
万方数据
维普
