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

Murthad Al-Yoonus, M. S. Jawad, M. F. Abdullah, Fares Al-Shargie
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引用次数: 7

Abstract

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.
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使用2D/3D图像处理算法加强敏感工业产品的质量控制管理
角点检测和敏感零件特征提取方法在自动化工业敏感产品制造的质量控制中越来越受到关注。由于二维边缘缺陷检测算法具有不支持和不准确的局限性,3D可以显著提高产品缺陷检测的精度。通过与二维边缘缺陷检测的比较,证明了三维边缘缺陷检测的精度。边缘缺陷检测的百分比已被证明有助于在交付阶段前接受或拒绝最终产品成型的决策。结果表明,在许多情况下,三维边缘缺陷检测比二维边缘检测算法更有助于决策。
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