The conventional self-adaptive Canny algorithm is not ideal for edge detection of hydrophobicity images

because the detected images often have many edge breakpoints

which prevent the forming of complete closed edge.In order to overcome the difficulty in capturing the upper edge of water droplets in hydropyobic images of insulators

this paper propose an improving canny algorithm by optimizing the filtering

threshold selection

and edge connectivity directions

respectively. Firstly

the image is pre-processed by combining adaptive histogram equalization with limited contrast and guided filteringand smoothed by bilateral filtering. Subsequenlythe two-dimensional OTSU and edge connection segmentation image are introduced in the Canny algorithm for image segmentation. Finally

the maximum water drop area ratio method is applied to determine the water repellency rating of the composite insulator image. The experimental results show that this method can accurately and effectively segment the hydrophobicity image

which provides a basis for the subsequent determination of hydro-phobicity.