基于机器视觉的大尺寸零件测量方法研究综述
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江苏理工学院机械工程学院 常州 213001

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TP391

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国家自然科学基金(51905235)、江苏省自然科学基金(BK20191037)、常州市科技计划项目(CJ20190069)、江苏省研究生实践创新计划项目(SJCX20_1045)、江苏理工学院研究生实践创新计划项目(XSJCX20_32)资助


Review of measurement methods of large-size parts based on machine vision
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School of Mechanical Engineering, Jiangsu University of Technology, Changzhou 213001, China

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    摘要:

    随着工业化水平的不断提高,基于机器视觉的大尺寸零件测量技术成为研究的热点。首先阐述了机器视觉测量技术的研究背景以及国内外研究现状,指出目前视觉测量研究的难点,提倡通过研究图像处理算法来提高测量精度和效率。其次,对视觉测量中广泛运用的边缘检测技术进行了调研分析,其主要采用粗精定位相结合的边缘检测算法,并重点分析了精确边缘定位中的亚像素边缘检测算法。接着,对大尺寸零件测量中所用到的图像拼接技术进行了调研分析,该技术所应用的图像配准主要基于区域和特征两类方法,并分析了两类方法的优势与不足。最后,总结了大尺寸零件测量方法的特点与局限性,并指出未来进一步探索的方向。

    Abstract:

    With the continuous improvement of the industrialization level, the measurement of large-size parts based on machine vision has been hot in research. Firstly, this paper explains the research background of machine vision measurement technology and the current research status at home and abroad, points out the difficulties of current vision measurement research, advocates to improve measurement accuracy and efficiency by studying image processing algorithms. Secondly, this paper researches the edge detection technology, which mainly uses the coarse and fine positioning edge detection algorithm in vision measurement. Sub-pixel edge detection algorithms in precise edge positioning are highlighted for analysis. Then, the image stitching techniques used in the measurement of large size parts are investigated and analyzed. The image registration applied by this technology is mainly based on two types of methods: region and feature. This paper also analyzes the advantages and disadvantages of these two types of methods. Finally, the characteristics and limitations of the measurement methods for large size parts are summarized, and future further exploring directions for improvement are pointed out.

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唐寒冰,巢 渊,刘文汇,马成霞.基于机器视觉的大尺寸零件测量方法研究综述[J].电子测量技术,2021,44(17):33-40

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  • 在线发布日期: 2024-08-09
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