To Identify Hot Spots in Power Lines Using Infrared and Visible Sensors

The detection of power transmission lines is highly important for threat avoidance, especially when aerial vehicle fly at low altitude. At the same time, the demand for fast and robust algorithms for the analysis of data acquired by drones during inspections has also increased. In this paper, different methods to obtain these objectives are presented, which include three parts: sensor fusion, power line extraction and fault detection. At first, fusion algorithm for visible and infrared power line images is presented. Manual control points describe as feature points from both images were selected and then, applied geometric transformation model to register visible and infrared thermal images. For the extraction of power lines, we applied Canny edge detection to identify significant transition followed by Hough transform to highlight power lines. The method significantly identify edges from the set of frames with good accuracy. After the detection of lines, we applied histogram based thresholding to identify hot spots in power lines. The paper concludes with the description of the current work, which has been carried out in a research project, namely SCIADRO.