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基于机器视觉的易拉罐打标区域定位方法
引用本文:侯松青,刘波,付作政,李玮.基于机器视觉的易拉罐打标区域定位方法[J].包装工程,2020,41(19):245-251.
作者姓名:侯松青  刘波  付作政  李玮
作者单位:中北大学 机械工程学院,山西 太原 030051
基金项目:山西省研究生教育创新项目(2019SY421)
摘    要:目的 为了提高易拉罐打标效率和打标位置精度,降低劳动强度,提出一种基于机器视觉的易拉罐打标区域定位方法。方法 首先建立模板库,获取即将打标的不同图案的易拉罐表面图像,对图像进行柱面反投影,使有一定弧度的图像展开,并利用模板匹配原理对图像进行拼接,得到易拉罐表面完整图像;其次采用ORB算法在模板库中确定易拉罐表面图案种类,利用模板匹配方法确定该种类图案的打标区域在待打标易拉罐上的位置,从而进行定位打标。结果 实验结果表明,该方法能实现直径为40~65 mm易拉罐的打标区域快速定位,定位误差为±2°。结论 基于机器视觉的易拉罐打标区域定位方法能实现易拉罐打标过程的自动化,可以快速、准确地定位出打标区域,且灵活性较高,降低了劳动成本,能满足企业的生产加工需要。

关 键 词:机器视觉  区域定位  易拉罐打标  模板匹配
收稿时间:2020/3/10 0:00:00
修稿时间:2020/10/10 0:00:00

Marking Area Positioning Method for Cans Based on Machine Vision
HOU Song-qing,LIU Bo,FU Zuo-zheng,LI Wei.Marking Area Positioning Method for Cans Based on Machine Vision[J].Packaging Engineering,2020,41(19):245-251.
Authors:HOU Song-qing  LIU Bo  FU Zuo-zheng  LI Wei
Affiliation:School of Mechanical Engineering, North University of China, Taiyuan 030051, China
Abstract:The paper aims to propose a marking area positioning method based on machine vision to improve the effi-ciency and positioning accuracy of marking, and reduce the labor intensity. Firstly, a template database was established to obtain the surface image of the cans with different patterns to be marked, and then the image was back projected on the cylinder surface to expand the image with a certain radian, and the image was spliced by the template matching principle to get the complete image of the can surface; secondly, ORB was used to determine the types of the cans surface pattern in the template database, and the template matching method was used to determine the position of the marking area of the type pattern on the can to be marked. The experimental results showed that the method can locate the marking area of 40-65 mm can quickly, and the error range was ±2°. Marking area positioning method for cans based on machine vision can realize the automation of the marking process, locate the marking area quickly and accurately. It has high flexibility, reduces the labor cost, and meets the production and processing needs of enterprises.
Keywords:machine vision  area positioning  can marking  template matching
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