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Visual Detection System Design for Plastic Infusion Combinations Containers Based on Reverse PM Diffusion

机译:基于逆向PM扩散的塑料输液组合容器视觉检测系统设计

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摘要

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%.
机译:针对医用PP输液中的黑斑,毛发,气泡等缺陷,提出了一种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,然后使用反向PM扩散算法来增强缺陷区域,在二值化后通过差异提取该区域,并对图像进行滤波。其次,使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,该方法具有较高的检测精度,所需的训练样本较少,适用于不同缺陷类型,准确率达95%。

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