Automatic Classification of Transmission Lines Based on Edge Detection Filtering Algorithm and Laser Point Cloud Data Processing.

Aiming at the problem of low automation and accuracy of semantic segmentation of transmission line point cloud data, an automatic segmentation algorithm of point cloud data that can extract objects such as towers, ground wires, and conductors is proposed based on the spatial feature distribution and edge detection filtering algorithm of the transmission line. The power plant is being tested using cloud data from the overhead power line LiDAR obtained from a drone. The results show that the algorithms proposed in this document have high accuracy and memory. The precision of the tower, conductor, and ground wire is 99.74%, 99.22%, and 97.69%, respectively, and the recall is 95.08%, 100%, and 97.97%, respectively. The classification effect is better than the commonly used automatic classification software of transmission line point cloud. Therefore, it has significant application value for realizing the accurate extraction of power lines and towers in transmission line point cloud data. [ABSTRACT FROM AUTHOR]