Aiming at the difficulty of side crack detection of cylindrical honeycomb ceramics, a detection method based on machine vision is proposed. Through the demand analysis of side crack detection, COMS camera and LED white parallel light source are selected. The collected image is filtered, and the median filter is selected to remove salt and pepper noise. According to the characteristics of the image, the ROI region is selected, the global threshold segmentation operator threshold is used for image segmentation, and the expansion method is used to connect the fracture region. When extracting surface defects, the connection operator is used to segment the image region, and then three features of area, length and width are selected to extract surface defects. The test results show that when there are 50 samples, the time required for qualified, unqualified and mixed samples by this method is 12.50 min, 6.64 min and 10.58 min respectively, which has higher detection speed and better real-time performance; The accuracy rates are 96%, 84% and 90% respectively. The accuracy rate needs to be improved and needs further research.