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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零件尺寸检测系统的边缘检测研究

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摘要

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零件尺寸检测系统的边缘检测,对边缘检测的对比研究进行了研究。将高斯模糊模拟图像和薄板零件图像作为评估图像,并使用Roberts算子,Sobel算子,Prewitt算子,Kirsch算子,Laplacian算子,LOG算子和数学形态学边缘检测方法进行边缘检测。对边缘检测结果进行了深入分析,比较了每种算法的边缘定位精度,抗噪能力和计算时间。采用数学形态学边缘检测方法获取单像素宽度连接轮廓,检测时间分别为0.0521秒和0.457秒。将数学形态学边缘检测方法作为基于机器视觉的薄板零件尺寸检测系统的边缘检测方法是合适的。

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