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Application of machine vision in edge burr measurement
During the manufacturing process , the cutting surface of most components would remain burr . This would affect the external surface and functionality of the product . Producers should identify this defect and strive to maintain quality , so we should establish a method to inspect burr .
Traditionally , the measurement tool of burr is our naked eyes . The disadvantage of this method is unnoticeable error caused by human . In order to avoid this drawback , we can take advantage of the machine vision system . First , compare the contours of the two 2D images , which are taken before and after the workpiece has been machined. Second , find the highest location of burr in precision of sub-pixel with our approach presented in this paper . This could be done according to the difference between contours . Finally, transfer the value of sub-pixel to the real height of burr by making use of the mapping function established in the calibration process .
When the burr had not rolled seriously , the error of machine vision was between -0.01mm and 0.01mm in our experiment .
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