Abstract:For the grafting process of modern agricultural automated grafting machine, grafting clips still requires the use of rigid shakers or manual involvement, and the overall automation degree needs to be improved, proposing a machine vision-based grafting clip gripping point positioning and orientation angle detection method; Designed a grafting clip for automated grafting, using backlighting method, calculating Hu moment for each shadow contour, and classifying according to Hu moment matching value to get the correct individual contour of grafting clip; Contour chain angle analysis is applied to each grafting clip individual contour to obtain the pixel position of the grafting clip gripping point; Calculate the orientation angle based on the gripping point position information; The experimental results show that the grafting clip average positioning error of grafting clip gripping point is 2.16 pixels, and the orientation angle detection error is 0.40 degrees; This method allows accurate visual inspection of grafting clips and is valuable in machine vision for the automatic sorting of grafting clips in the grafting process of grafting machines.