Image Identification Method of Ice Thickness on Transmission Line Based on Visual Sensing

In order to obtain high precision image identification results of transmission line ice thickness, an image identification method of transmission line ice thickness based on visual sensing was proposed. The ice-covered images of transmission lines are collected by visual sensors, and we take the non-local self-similarity information of the images as a regularized prior constraint term, which is combined with K-SVD algorithm to establish an image denoising model to remove the noise in the images. The ice-covered regions of transmission lines are segmented in the image and the edge features of ice-covered regions are extracted; we can calculate Ice thickness based on regional pixels, and finally realized the image identification of transmission line ice thickness. After experimental testing, it has been proven that the signal-to-noise ratio of the denoised image using the proposed method is higher than 3.76 dB, which can effectively extract the grayscale features of the icing on the transmission line and obtain accurate identification results of the icing thickness. The deviation between the calculated icing thickness and the actual value is less than 0.05 mm, and the accuracy of icing thickness identification is high, which has strong engineering application value.