Abstract:The channel environment of high-voltage transmission line has a great impact on the safety of high-voltage lines. In the past, manual inspection of the channel environment was a necessary way. Nevertheless, the manual inspection is dangerous and difficult, and its efficiency is low. To solve the problem, we propose a super-pixel combined with deep neural network for high-voltage transmission line environment detection. First, we obtain the overall image of the channel environment by the splicing technique for UAV aerial photography. Then, we employ the super-pixel segmentation algorithm to preprocess the image, in which we choose the SURF descriptor to extract the superpixel features because of its rapidity and effectiveness. Finally, the deep neural network model is used for training and classification and the superpixels are classified to achieve the purpose of detection. The experimental results on real environment images show that the inspection efficiency of high-voltage transmission line channel environment is greatly improved and the proposed algorithm is effective.