A New Detection Method of Overhead Power Line Based on HED Algorithm

Power line detection is an important content of power system inspection, which of important significance for UAV inspection, obstacle avoidance, and visual measurement. Traditional power line detection algorithms are mostly based on straight line detection, and the power lines are further extracted from the detected straight lines. Therefore, the disturbance of background information is large, and the detection effect for curved lines is not satisfied. Classical deep learning object detection algorithms are not suitable for the detection of elongated objects such as overhead power lines. Based on the Holistically-Nested edge detection (HED) algorithm, this paper uses the Tensorflow deep learning framework to build a HED network model and train it. Through pixel-level classification of the image, the pixel-level segmentation of the wires in the image is realized. Through experimental verification, the power line detection achieves a high accuracy rate.