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Research on edge detection of thin sheet part dimension inspection system based on machine vision

机译:基于机器视觉的薄板部尺寸检测系统边缘检测研究

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Aiming at the edge detection of thin sheet part dimension inspection system based on machine vision, a contrast research on edge detection is investigated. The Gaussian blurred simulation image and thin sheet part image are took as evaluation images, and the edge detection are done with Roberts operator, Sobel operator, Prewitt operator, Kirsch operator, Laplacian operator, LOG operator and mathematical morphology edge detection method. The results of edge detection are analyzed deeply, and the edge location accuracy, noise resisting ability and calculation time of each algorithm are compared. The single-pixel width connected contour is acquired with mathematical morphology edge detection method, the detection time are 0.0521 second and 0.457 second respectively. It is appropriate that taking the mathematical morphology edge detection method as the edge detection method of thin sheet part dimension inspection system based on machine vision.
机译:针对基于机器视觉的薄板部尺寸检测系统的边缘检测,研究了对边缘检测的对比度研究。高斯模糊的仿真图像和薄板部图像作为评估图像,并且边缘检测与Roberts运算符,Sobel运算符,Prowitt运算符,Kirsch操作员,拉普拉斯算子,日志操作员和数学形态边缘检测方法进行了评估图像。深度分析边缘检测结果,比较了每个算法的边缘定位精度,噪声能力和计算时间。单像素宽度连接轮廓以数学形态边缘检测方法获取,检测时间为0.0521秒和0.457秒。基于机器视觉的薄板部尺寸检测系统的边缘检测方法,采用数学形态学边缘检测方法是合适的。

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