基于视觉的塑料颗粒混合色检测。

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2024-09-01 DOI:10.1063/5.0228741
Yinyin Yu, Huaishu Hou, Zhifan Zhao, Hongsheng Xu, Zhao Fan, Shuaijun Xia, Chaofei Jiao, Xinru Li
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引用次数: 0

摘要

在高端 PP-R 管材的生产过程中,不同颜色的原材料颗粒混合会导致最终产品颜色不均,影响其外观质量。针对这一问题,我们提出了一种基于图像处理技术的可视化无损检测解决方案。该解决方案旨在通过减少背景干扰和在各种环境中进行自适应调整来提高检测效率和准确性。首先,采用 K-Means 图像分割算法消除原始图像中的复杂背景因素,显著提高图像分割精度。随后,利用高斯混合模型算法自动提取去除背景后前景图像的颜色阈值,方便算法的自适应调整。最后,引入平均值算法,利用自动获取的颜色阈值快速准确地识别不同颜色的塑料颗粒。实验结果表明,这种方法可以快速准确地识别不同颜色的颗粒,并有效地支持杂质颗粒的剔除。通过这种方法,算法的平均检测准确率达到了 99.3%。
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Vision-based mixed color detection of plastic particles.

In the production process of high-end PP-R pipes, mixing different colored raw material particles can result in uneven color in the final product, affecting its appearance quality. in addition, color mixing can reduce the physical properties of the pipes, impacting their durability and safety. To address this issue, we propose a visual, non-destructive inspection solution based on image processing technology. The solution aims to enhance detection efficiency and accuracy by reducing background interference and enabling adaptive adjustments in various environments. Initially, the K-Means image segmentation algorithm is employed to eliminate complex background factors from the original image, significantly improving image segmentation accuracy. Subsequently, the Gaussian mixture model algorithm is utilized to automatically extract the color threshold of the foreground image after background removal, facilitating adaptive algorithm adjustments. Finally, the mean value algorithm is introduced to swiftly and accurately identify plastic particles of different colors using the automatically obtained color thresholds. Experimental results demonstrate that this method can quickly and accurately identify different color particles and effectively support the rejection of impurity particles. Through this approach, the algorithm achieves an average detection accuracy of 99.3%.

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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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