An embedded vision ranging system is designed and developed to solve the problem of workpiece positioning. Firstly, this paper has a theoretical analysis of distance measuring based on binocular vision. Then proposing an improved stereo matching algorithm CSGM based on SGM. Also having an algorithm performance testing for CSGM on its accuracy of stereo matching and time consumption based on the Middlebury datasets by using the evaluation toolkit MiddleEval3. After the stereo calibration of the binocular camera and rectifying the stereo image pair, a distance-measuring experiment was carried out, showing the embedded vision ranging system has a millimeter precision for positioning workpieces.
In order to better segment the sandstone particles, this paper improves the traditional image acquisition method by adding a baffle plate and a divider plate to collect the cohesive sandstone images. The collected images are processed by a series of OpenCV libraries in the computer, including grayscale and grayscale equalization, filtering noise reduction, binarization, morphological optimization and image segmentation based on the improved watershed algorithm. In the sandstone particle segmentation experiment, By comparing the results obtained by the image method with the results obtained by the manual screening method, the experimental results show that the image method proposed in this paper can effectively segment the real sandstone particles in the sandstone segmentation of the mixing production line, and the availability of this method is very high, meeting the industrial requirements.
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