基于PM反向扩散的塑料输液组合容器视觉检测系统设计

Hui Zhang, T. Shi, Shi-Qiang He, Haizhou Wang, Feng Ruan
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引用次数: 1

摘要

针对医用PP输液中存在的黑点、毛状、气泡等缺陷,提出了基于机器视觉的输液缺陷检测系统。首先设计机械执行器、电气控制和图像采集系统,然后利用反向PM扩散算法对缺陷区域进行增强,二值化后通过差值提取缺陷区域,对图像进行滤波。其次,利用支持向量机对缺陷和缺陷区域进行自动分类;同时,为了提高分类器的性能,本文选择了基于交叉验证的最佳分类参数。结果表明,该方法检测准确率高,所需训练样本少,适用于不同的缺陷类型,准确率达到95%。
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Visual Detection System Design for Plastic Infusion Combinations Containers Based on Reverse PM Diffusion
Aimed at the defect of black spots, hair, bubbles in medical PP infusion, infusion defect detection system based on machine vision is proposed. Firstly, r design the mechanical actuators, electrical control, and image acquisition system, then use reverse PM diffusion algorithm to enhance the defect area, extracting this area by difference after binarization, and filter the image. Secondly, SVM is used to classify defects and the defective area automatically. Meanwhile, in order to improve the performance of the classifier, the paper selected the best classification parameters based cross validation. The results show that the method is high detection accuracy and requires less training samples, applies to different defect types with accuracy rate of 95%.
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