Aiming at noise and pseudo-edge interference in the edge extraction process of automobile coating images caused by the complex environment and uneven lighting in production plants, an edge extraction algorithm for automobile coating images with an improved Canny operator is proposed. Firstly, the algorithm adopts a cascade filter composed of a multi-level median rational hybrid filter and a guided filter to denoise and smooth the image, while retaining the target edge information during noise reduction. Secondly, the improved Sobel operator convolution template is applied to extract the gradient vectors from four directions of horizontal, vertical, 45°, and 135°, so as to improve edge localization accuracy. Finally, in the edge connection stage, the improved Otsu method (maximum interclass variance method) is used to select high and low thresholds, increasing the adaptability of the algorithm. Experimental results show that in terms of image denoising, compared with traditional median filtering, the algorithm ensures that the peak signal-to-noise ratio of the denoised image is higher than 35 dB, and the structural similarity is greater than 0.9. The overall peak signal-to-noise ratio increases by more than 6%, and the structural similarity is improved by more than 6.5%. In the aspect of edge extraction, it can effectively reduce the interference of the pseudo-edge and has a high degree of edge connectivity.