Power line detection via background noise removal
Tiny target detections, especially power line detection, have received great attention due to its critical role in ensuring the flight safety of low flying unmanned aerial vehicles (UAVs) In this paper, an accurate and robust power line detection method is proposed, wherein background noise is mitigated by an embedded convolution neural network (CNN) classifier before conducting the final power line extractions. Our proposed method operates in three steps: 1) extract edge features of power lines from a testing image, 2) employ a CNN classifier to remove the background noise, 3) use a Hough Transform (HT) based fine selection module to locate power lines. Comprehensive experiments demonstrate the superiority of the proposed method, compared to the state of the art methods.
2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)