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Enhance quality control management for sensitive industrial products using 2D/3D image processing algorithms

机译:使用2D / 3D图像处理算法增强敏感工业产品的质量控制管理

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Corners detection and sensitive parts features extractions methods are gaining more interests in quality control for automated industrial sensitive products manufacturing. As 2D edge defections detections algorithms have their own limitation as they are not supportive and accurate, 3D can improve significantly the accuracy of detecting the product defects. This paper, proof the concept of the accuracy of using 3D edge defections detection in comparison with 2D. Percentages of edge defection detections have been shown to aid the decision making of accepting or rejecting the final products shaping before delivery stage. Results showed that in many cases, 3D edge defections detections aid the decision making better than 2D edge detections algorithms.
机译:角落检测和敏感部件特征提取方法对自动化工业敏感产品制造的质量控制产生更多兴趣。 由于2D边缘缺陷检测算法具有自身限制,因为它们不支持且准确,3D可以显着提高检测产品缺陷的准确性。 本文证明了使用3D边缘缺陷检测的准确性的概念与2D相比。 已经示出了边缘缺陷检测的百分比,以帮助决策接受或拒绝在交付阶段之前塑造的最终产品。 结果表明,在许多情况下,3D边缘缺陷检测有助于决策优于2D边缘检测算法。

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