In order to detect and analyze the safety of high voltage transmission lines, based on airborne light detection and rangring(LiDAR) power corridor data, a segmentation and extraction algorithm of power line laser point cloud was proposed based on density-based spatial clustering of applications with noise (DBSCAN). This method can realize fast segmentation and extraction of single power line in transmission corridor. Firstly, the point cloud of power line was projected on the x-O-y plane. The projected laser points were fitted linearly by the least square method. Secondly, after calculating the length of transmission corridor, empirical parameters were used to segment power line point clouds. Then, DBSCAN was applied to segment point clouds in the projection plane. Finally, the classification of segmentation clustering results was normalized and the laser point cloud data of a single power line was obtained. The results show that, with this method, fast and accurate segmentation and extraction of power line laser point cloud can be obtained when the piecewise width of the empirical parameter is only needed. According to the segmentation results, the distance between the power line and the objects in the power corridor is calculated and the type and distance of dangerous points can be judged. By comparing and verifying the experiment with the field measurement results, the proposed method has high extraction and measurement accuracy. It can be effectively applied to power line safety detection and analysis.