杨健,豆昌军,辛浪,柳伟兵,周鑫.视觉匹配技术的药片颗粒计数算法研究[J].包装工程,2018,39(19):175-180.
YANG Jian,DOU Chang-jun,XIN Lang,LIU Wei-bing,ZHOU Xin.Tablet Counting Algorithm Based on Visual Matching Technology[J].Packaging Engineering,2018,39(19):175-180. |
| 视觉匹配技术的药片颗粒计数算法研究 |
| Tablet Counting Algorithm Based on Visual Matching Technology |
| 投稿时间：2018-04-06 修订日期：2018-10-10 |
| DOI：10.19554/j.cnki.1001-3563.2018.19.031 |
| 中文关键词: 机器视觉 药片计数 边缘检测 模板匹配 图像金字塔 |
| 英文关键词: machine vision tablet counting edge detection template matching image pyramid |
| 基金项目:成都理工大学机械工程专业教学创新团队项目（10912-JXTD201501）；成都理工大学智能制造学科项目（10800-17Z0620） |
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| 中文摘要: |
| 目的 通过机器视觉技术解决当前医药产业迅猛发展带来的批量生产药粒无法高效、精确计数等难题，提出基于视觉技术的药片特征二次匹配算法。方法 药粒预处理后分割为多连通域，采用面积特征选择形状特征差异较大的2颗药粒为感兴趣区域，待膨胀后作为目标的先验模型，Canny算子提取边缘轮廓，同时计算轮廓点的方向向量。采用3层图像金字塔搜索算法加快匹配效率，并用最小二乘法调整模板的匹配精度，使匹配精度达到亚像素级别。结果 通过对不同的椭圆形药粒进行实验分析，将匹配模板1和模板2（缩放比为1∶1）的最小匹配分数阈值分别设为0.63和0.59，采用3层图像金字塔搜索算法，从创建模板到匹配计数只需要0.11 s，相较于3层金字塔（缩放比为0.7~1.0，最小匹配分数为0.6）的单模板匹配算法速度快0.07 s，且对部分重叠的药片仍能有效计数，匹配准确率达100%。结论 采用药片颗粒二次匹配技术可实现检测速度上的扩增；采用图像金字塔搜索算法可大幅度缩减匹配时间；采用最小二乘法可提高模板的匹配精度，增大药粒匹配的正确率。 |
| 英文摘要: |
| The work aims to propose a secondary matching algorithm of tablet features based on vision technology, to solve the problem of inability to efficiently and accurately count mass produced tablets due to the rapid development of the current pharmaceutical industry by means of machine vision technology. Firstly, the tablets were preprocessed and divided into multiple connected regions. Then, two tablets with large differences in shape features were selected as regions of interest with the area characteristics, and they were inflated to become the targeted prior model. The edge contour was extracted by the Canny operator, and the direction vectors of the contour points were calculated. The three-tier image pyramid search algorithm was used to speed up the matching accuracy, and the least square method was applied to adjust the matching accuracy of the template, so that the matching accuracy reached the sub-pixel level. Based on the experimental analysis of different elliptical tablets, the minimum matching score thresholds that matched templates 1 and 2 (scaling was 1:1) were respectively set as 0.63 and 0.59. With the three-tier image pyramid search algorithm, it only took 0.11 s to match the count from the creation of template. Compared with the thee-tier pyramid, the scaling was 0.7-1.0, the single-template matching algorithm speed with the minimum matching score of 0.6 was 0.07 s faster, and it could still effectively count part of the overlapped tablets with the matching accuracy of 100%. The secondary matching technology of the tablets can amplify the detection speed. The image pyramid search algorithm can be used to greatly shorten the matching time and the least square method can be applied to improve the matching accuracy of the template and increase the matching accuracy of the tablets. |
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