3D Detection of Power-Transmission Lines in Point Clouds Using Random Forest Method

Inspection of power transmission lines using classic experts based methods suffers from disadvantages such as highel level of time and money consumption. Advent of UAVs and their application in aerial data gathering help to decrease the time and cost promenantly. The purpose of this research is to present an efficient automated method for inspection of power transmission lines based on point clouds achieved by aerial data. The proposed method followed by five steps: removing noise on point clouds and filtering point clouds in order to divide it into two parts of ground points and non-ground points, features extraction from non-ground point clouds and finally, power lines classified for 3d detection of power lines. For capability assessment of the proposed method, wo different data sets as aerial RGB based UAV imagery ad aerial laser based data is applied. Accuracy of the proposed method was 97.05% in total classification and 98.80% in power lines detection for dataset 1 taken over an urban area with spectral features. The total accuracy in classification was 95.48% and 96.81% in power lines detection for dataset 2 that taken from a rural area.