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| 药品生产线瓶盖缝隙的视觉检测技术研究 |
| Vision inspection for gap of cap in the drug production line |
| 投稿时间：2015-10-13 |
| DOI：10.3969/j.issn.1005-5630.2016.04.001 |
| 中文关键词: 视觉检测 瓶盖缝隙 在线自动化 |
| 英文关键词:vision inspection gap of cap online automation operation |
| 基金项目:国家自然科学基金项目（61405052，61378035） |
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| 摘要点击次数: 3297 |
| 全文下载次数: 180 |
| 中文摘要: |
| 结合药品生产线瓶盖缝隙检测的具体需求，提出一种视觉成像采集系统的筛选与设计思路以及在此基础上的视觉图像处理方法。分析了视觉图像信息采集系统与具体生产线需求的关系，确定了图像采集系统的参数，设计了透射式照明与成像采集系统架构。在获取视觉图像后，提出使用区域标记算法、canny边缘检测算法、黑白二值化算法等，自动寻找瓶盖区域并确定瓶盖缝隙的像素宽度，最终给出实际物理宽度。测试实验表明，该系统测量的准确率为100%，最大误差值为0.016 mm，最大误差百分比为2.73%，平均误差百分比为1.15%。 |
| 英文摘要: |
| According to demand of gap detection of cap in the drug production line,a method was proposed to solve the problem.The proposed method includes the selection and design for visual imaging system,and the image processing algorithm based on the system.The relationship between visual image capture system and production line was analyzed.The authors determined the parameter of image capture system and designed the structure of transillumination and image acquisition system.After the acquisition of the image,region labeling algorithm,and the canny edge detection algorithmbinary algorithm were used to automatically search the cap area and calculate the width of pixels of the gap.Finally,the actual physical width was obtained from the pixels width.The experimental results demonstrate that the accuracy of the propose method is 100%,and the maximal error is 0.016 mm.The results also give out that the maximal error 2.73%,and the average error is 1.15%. |
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