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| 论文编号: |
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| 第一作者所在部门: |
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| 中文论文题目: |
A System for Automated Detection of Ampoule Injection Impurities
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| 英文论文题目: |
A System for Automated Detection of Ampoule Injection Impurities
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| 论文题目英文: |
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| 作者: |
Ge, Ji
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| 论文出处: |
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| 刊物名称: |
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
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| 年: |
2017
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| 卷: |
14 |
| 期: |
2 |
| 页: |
1119-1128 |
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| 摘要: |
Ampoule injection is a routinely used treatment in hospitals due to its rapid effect after intravenous injection. During manufacturing, tiny foreign particles can be present in the ampoule injection. Therefore, strict inspection must be performed before ampoule injections can be sold for hospital use. In the quality control inspection process, most ampoule enterprises still rely on manual inspection which suffers from inherent inconsistency and unreliability. This paper reports an automated system for inspecting foreign particles within ampoule injections. A custom-designed hardware platform is applied for ampoule transportation, particle agitation, and image capturing and analysis. Constructed trajectories of moving objects within liquid are proposed for use to differentiate foreign particles from air bubbles and random noise. To accurately classify foreign particles, multiple features including particle area, mean gray value, geometric invariant moments, and wavelet packet energy spectrum are used in supervised learning to generate feature vectors. The results show that the proposed algorithm is effective in classifying foreign particles and reducing false positive rates. The automated inspection system inspects over 150 ampoule injections per minute (versus by technologist) with higher accuracy and repeatability. In addition, the automated system is capable of diagnosing impurity types while existing inspection systems are not able to classify detected particles. |
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