【摘要】 针对现有的工件测量装置普遍存在精度低、范围小和效率低等问题，利用高精度图像采集模块，以机器视觉为核心，结合优化后的SURF特征点匹配和最小二乘法拟合等算法，提出可对大尺寸工件的孔洞和边线等参数进行高精度测量分析的系统。该系统可在35 s内对1 m大小的工件以微米级别的误差进行测量，相比传统检测方法，具有高精度和高效率的优点，且适用于大尺寸工件检测的要求，为工件测量行业提供一种新的检测方案。更多还原

【Abstract】 This paper aims at the general problems of low precision, small range and low efficiency in the existing measuring devices for workpiece. In this paper, utilizing a high-precision image acquisition module, with machine vision as the core, combined with optimized SURF feature point matching and least-square fitting algorithms, a system for high-precision measurement and analysis of the parameters such as holes and edges of large-size workpiece is proposed. The system is capable of measuring 1-meter workpiece in 35 s with a micron-level error. Compared with the traditional detection method, it has the advantages of high precision and high efficiency, and it is suitable for the detection of large size workpiece, which provides a new detection scheme for the workpiece measurement industry.更多还原