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Research on Recognition Method of Zinc Dross in Hot Dip Galvanizing Pot Based on Image Feature

机译:基于图像特征的热镀锌锅锌渣识别方法研究

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To realize the automatic removal of zinc slag in a hot-dip galvanizing pot, the recognition method of zinc slag based on features was studied. Three recognition algorithms of zinc slag based on image pixel value, SSIM (Structural Similarity Index), and image features are designed. MATLAB was used for experimental simulation, and the accuracy, precision, recall, F1- score, and execution efficiency of the three methods were compared. The results show that the zinc slag recognition method based on pixel value is more comprehensive, and the zinc slag recognition method based on statistical features has the highest accuracy, while the zinc slag recognition method based on SSIM has the best comprehensive effect in recognition.
机译:为了实现热镀锌锅中锌渣的自动去除,研究了基于特征的锌渣识别方法。设计了三种基于图像像素值、结构相似性指数和图像特征的锌渣识别算法。利用MATLAB进行实验仿真,比较了三种方法的准确度、精确度、召回率、F1评分和执行效率。结果表明,基于像素值的锌渣识别方法更全面,基于统计特征的锌渣识别方法准确率最高,而基于SSIM的锌渣识别方法综合识别效果最好。

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