Research on Dimensional Measurement Based on Sub-pixel Edge Detection

Weidong Yang, Jiaxing Wang, K. Peng, Dan Sun
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Abstract

With the development of modern industry, image measurement technology with its high speed ,high precision and non-contact advantages receives high-profile attention. In the machine vision system the size of the process of mechanical parts measured, it is found that the accuracy of the edge position directly influence the accuracy of the measurement results. According to the research on the current sub-pixels positioning of image processing technology, this paper firstly makes a theory analysis and research about sub-pixel location methods based on gray level moment theory and the theory of Gaussian fitting. Then through the parts size measurement experiment, under the premise of contrast location with classical edge detection operators, some groups of data are extracted respectively compared to both of the detection performance and accuracy.Thus it provided the reference for the sub-pixels edge detection algorithm in the actual application.
基于亚像素边缘检测的尺寸测量方法研究
随着现代工业的发展,图像测量技术以其高速、高精度和非接触的优点受到人们的高度重视。在机器视觉系统对机械零件尺寸进行测量的过程中,发现边缘位置的精度直接影响测量结果的精度。在对当前图像处理技术的亚像素定位研究的基础上,本文首先对基于灰度矩理论和高斯拟合理论的亚像素定位方法进行了理论分析和研究。然后通过零件尺寸测量实验,在与经典边缘检测算子进行对比定位的前提下,分别提取几组数据,对检测性能和精度进行比较。从而为亚像素边缘检测算法在实际应用中提供了参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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