结合实际的医用试纸生产中，存在着质检环节依靠人工肉眼检查，效率低下，误判率随工作时间推移而增加，并且还对生产工人有健康风险的现象，本文从硬件设备到软件算法上设计了一整套基于机器视觉的试纸自动质检系统，着重介绍改进传统的模板匹配算法，将模板匹配分为两个层级，使其在X、Y两个维度分级匹配搜索，并针对这一算法带来的计算量过大的副作用进行了搜索方法的优化，使得在较大视场(310 * 330 mm)的环境下，拥有较高的分辨精度(0.04 mm)，而且效率尚佳，从而在不增加产品的质检工序的时间上使得误判率显著降低。
In combination with the actual medical test paper production, there is a phenomenon where the quality inspection link relies on manual visual inspection; the efficiency is low; the misjudgment rate increases with the working time, and there is also a health risk to the production workers. This article goes from hardware equipment to software algorithms. A set of automatic inspection system for test strip based on machine vision was designed. The traditional template matching algorithm was improved. The template matching was divided into two levels to make the matching search in the X and Y dimensions. The calculation method is optimized due to the excessive side effects of calculation, so that the resolution is high (0.04 mm) at the same time in a large field of view (310 * 330 mm), and the efficiency is still good, so that it does not increase. The time of the quality inspection process of the product significantly reduces the misjudgment rate.
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Vock, R., Dieckmann, A., Ochmann, S. and Klein, R. (2019) Fast Template Matching and Pose Estimation in 3D Point Clouds. Computers & Graphics, 79, 36-45. https://doi.org/10.1016/j.cag.2018.12.007
