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Traditional burr detection methods are increasingly unable to meet the requirements of deburring in terms of accuracy and efficiency. In this paper, machine vision is adopted. Firstly, the image of the workpiece is preprocessed, and appropriate edge detection operators are selected to detect the basic edge of the burr. Then, the closed burr edge is generated by detecting the slow changing area with the regional growth. Finally, the edge is judged to be burr by comparing the contour and other methods. Experiments show that this method has the advantages of fast, high efficiency and strong stability in the study of burr detection, and can meet the requirements of the project.

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