Research On The System For High Precision Measurement Based On Machine Vision

Machine vision measurement technology has gradually penetrated into every field of industry in recent years, with its own advantages, such as rapid, non-contact and so on. For the purpose of the measuring system, the system accuracy should be the first factor to consider, guarantee the accuracy to ensure the credibility of the measurement. In order to improve the measurement accuracy of machine vision measuring system, This paper presented a formula of error compensation on the basis of the influence of light intensity on the measurement accuracy. Take the calibration board as the experiment object, this formula can reduce the error caused by light intensity of the system.In this paper, the machine vision technology, application field and development trend are briefly introduced, in order to meet the requirements of high precision measurement system, based on theoretical analysis and practical experience, on the analysis of the general pattern of machine vision measuring system, working principle, system composition based, discusses in detail how the hardware selection, the choice of the measurement system needs industrial camera, light source, lens, image acquisition card and so on. Set up a system to measure the experimental platform, realize the image measurement, calibration and other functions. In terms of system precision, this paper analyzed the main error factors affecting the measurement accuracy. The positioning error of the system structure caused by the light source and the lens plane is analyzed. Through the comparison of several methods to adjust the verticality of optical axis and object surface, this system adopted the method of calibration and the manual adjustment. Theoretical analysis and experimental verification of the impact of the change of illumination intensity on the accuracy of measurement. In order to evaluate the accuracy of the system, the pixel equivalent value of circular calibration template and the circle diameter of the calibration board are used as the evaluation index of the evaluation system. The equivalent value of the system is calculated by digital image processing method and the circle diameter of the calibration board is calculated. In this paper, an error compensation formula is proposed to compensate for the error caused by the change of illumination intensity. Experimental data shows that the accuracy of the method is improved by using this method.In this paper, the algorithm of edge detection is studied in this paper. Pixel level edge detection and sub-pixel edge location are studied. Several classical edge detection operators are introduced in the edge detection algorithm, this paper proposes a new method to find the edge of the edge detection algorithm based on the tracking method, which can not only suppress the noise, eliminate the false edge, but also improve the accuracy of the edge. In the sub pixel edge location method, a new method based on the combination of the cubic spline interpolation method and the Gauss surface fitting method is proposed. First, the image is segmented by using the cubic spline interpolation method, and then the edge of the image is extracted by using Gauss curve fitting.