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Noncontact 3-D Coordinate Measurement of Cross-Cutting Feature Points on the Surface of a Large-Scale Workpiece Based on the Machine Vision Method

机译:基于机器视觉方法的大型工件表面上的横切特征点的非接触式3-D坐标测量

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摘要

Three-dimensional coordinate measurement of feature points on the surface of a large-scale workpiece is important and difficult. Various relative measuring methods have been presented in recent years, and the machine vision method has been paid more attentions by researchers. The application of the machine vision method in 3-D coordinate measurement of feature points on the surface of a large-scale workpiece is discussed in this paper, and an accurate, simple, and new measuring method is proposed. The design of the measuring system mainly considers the following aspects: 1) the principle and composition of the measuring system; 2) the monocular vision algorithm for camera locating; 3) the calibration algorithm of the charge-coupled device (CCD) camera; 4) the image processing algorithm of cross-cutting feature points and the calculation of their 2-D image coordinates; and 5) the binocular stereo vision algorithm for depth measurement based on the large-scale coordinate measuring machine. The experimental results indicate the correctness and reliability of the new measuring method, and we believe that it will be a reliable and efficient technique for the noncontact 3-D coordinate measurement of cross-cutting feature points on the surface of a large-scale workpiece.
机译:大型工件表面上的特征点的三维坐标测量是重要的且困难。近年来介绍了各种相对测量方法,并且机器视觉方法由研究人员提供更多的注意。本文讨论了机器视觉方法在三维坐标测量中,在大规模工件表面上的特征点测量,提出了精确,简单,新的测量方法。测量系统的设计主要考虑以下几个方面:1)测量系统的原理和组成; 2)相机定位的单眼视觉算法; 3)电荷耦合器件(CCD)相机的校准算法; 4)交叉特征点的图像处理算法及其2-D图像坐标的计算; 5)基于大规模坐标测量机的深度测量双目立体声视觉算法。实验结果表明了新的测量方法的正确性和可靠性,我们认为这将是一种可靠而有效的技术,用于在大型工件表面上的横切特征点的非接触式3-D坐标测量。

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