基于机器视觉的包装品质检测系统设计

目的 为提高包装缺陷检测精度，基于机器视觉设计一种包装品质检测系统。方法 介绍机器视觉系统硬件结构，包括载物平台、工业相机、光室、计算机等。在此基础上，以条烟外包装检测为主要研究对象，详细阐述图像处理算法。首先利用中值滤波消除原始图像噪声;然后基于Canny算子实现图像边缘锐化;最终通过图像配准判断条烟外包装是否存在缺陷。结果 通过实验验证，结果表明该系统对合格样本的识别率可以达到100%;不合格样本的识别率也可以达到98.67%;整体识别率可以达到99.33%。结论 机器视觉系统具有识别精度高、性能稳定等特点;图像处理算法可准确区分条烟是否存在缺陷，具有实际应用价值。

Design of Packaging Quality Inspection System Based on Machine Vision

The work aims to design a packaging quality detection system based on machine vision to improve the accuracy of packaging defect detection. The hardware structure of machine vision system was introduced, including carrier platform, industrial camera, light room, computer, etc. On this basis, the image processing algorithm was described in detail with the detection of cigarette packaging as the main research object. First, the median filter was used to eliminate the original image noise. Then, the image edge was sharpened based on Canny operator. Finally, image registration was used to judge whether there ware defects in cigarette packaging. The validity of the system was verified by experiments, and the results showed that the recognition rate of the system to qualified samples could reach 100%. The recognition rate of unqualified samples could also reach 98.67%. The overall recognition rate was 99.33%. The machine vision system has the characteristics of high identification accuracy and stable performance. The image processing algorithm can accurately distinguish whether a cigarette has defects and has practical application value.