An Automatically Locating Method for Insulator Object Based on CNNs

In this paper, a method is proposed to locate the insulator automatically in aerial image based on binarized normed gradients (BING) and convolutional neural networks (CNNs). Firstly, we extract insulator candidate windows with BING algorithm. Secondly, we identify the windows containing insulator with convolution neural networks. Finally, the weighted iteration of the window set with high overlap is used to acquire the final insulator positioning results. The method proposed in this paper is validated with the transmission line aerial images obtained by the actual inspection of the large-scale unmanned helicopter of Guangdong Grid Co. Experiment shows that the recall of insulators with complex background is 90.5% and the positioning accuracy is 92%, which means the proposed method can effectively locate the insulators in aerial image with complex background, the method also has strong versatility, and can be adapted to the visible light image of different background.