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

被引：1
|
作者：
Chen Gang [1 ]
Dan Binbin [1 ]
Xiong Ling [2 ]
Chen Xiaoyan [3 ]
机构：
[1] Wuhan Univ Sci & Technol, Sch Machinery & Automat, Wuhan, Peoples R China
[2] Wuhan Univ Sci & Technol, Sch Informat Sci & Engn, Wuhan, Peoples R China
[3] Hubei Sci & Technol Coll, Sch Telecom Engn, Wuhan, Peoples R China
来源：
2021 4TH INTERNATIONAL CONFERENCE ON INTELLIGENT AUTONOMOUS SYSTEMS (ICOIAS 2021) | 2021年
关键词：
zinc slag feature; recognition algorithm; image hash;
D O I：
10.1109/ICoIAS53694.2021.00032
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：134 / 138
页数：5
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