基于改进GMS特征匹配算法的浮选泡沫移动速度特征提取

doi:10.11896/jsjkx.211000064

计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 211000064-6.doi: 10.11896/jsjkx.211000064

• 图像处理&多媒体技术 • 上一篇下一篇

基于改进GMS特征匹配算法的浮选泡沫移动速度特征提取

刘惠中^1,2, 余华富¹, 彭志龙¹

1 江西理工大学机电工程学院江西赣州 341000
2 江西省矿冶机电工程技术研究中心江西赣州 341000

出版日期:2022-11-10 发布日期:2022-11-21
通讯作者: 刘惠中(huizhong6@163.com)
基金资助:
江西省“千人计划”引进创新高层次人才项目(JXSQ2018101046)

Feature Extraction of Flotation Foam Moving Speed Based on Improved GMS Feature Matching Algorithm

LIU Hui-zhong^1,2, YU Hua-fu¹, PENG Zhi-long¹

1 School of Mechanical and Electrical Engineering,Jiangxi University of Science and Technology,Ganzhou,Jiangxi 341000,China
2 Jiangxi Mining and Metallurgy Electromechanical Engineering Technology Research Center,Ganzhou,Jiangxi 341000,China

Online:2022-11-10 Published:2022-11-21
About author:LIU Hui-zhong,born in 1969,Ph.D,professor,Ph.D supervisor.His main research interests include mining and metallurgy equipment and intelligence.
Supported by:
Jiangxi Province “Thousand Talents Plan” Introduction of Innovative High-level Talents Project(JXSQ2018101046).

摘要/Abstract

摘要： 矿物浮选过程中,浮选泡沫移动速度与浮选过程的控制之间存在着较大的关联性,如能实时准确地获取泡沫移动速度等动态特征可以为浮选过程的液位、加药量、充气量等控制参数的优化调整提供依据。为了有效地获取浮选泡沫的移动速度,文中提出了一种基于改进GMS特征匹配算法的浮选泡沫移动速度特征提取方法。首先采用ORB算法提取并描述泡沫的特征点,再利用GMS特征匹配算法完成特征点对的快速匹配,在以上基础上再利用RANSAC算法对特征匹配结果中存在的误匹配点进行剔除,最后通过计算泡沫特征点的位移进而得到泡沫移动速度。经过对采集到的工业图像数据进行应用测试表明,所提算法不但解决了传统算法在浮选泡沫图像特征提取中存在误匹配点多的问题,还有效提升了浮选泡沫特征提取的效率和稳定性。

关键词: 浮选泡沫图像, ORB算法, GMS特征匹配, RANSAC算法, 泡沫移动速度提取

Abstract: In the process of mineral flotation,there is a great correlation between the moving speed of flotation foam and the control of flotation process.If the dynamic characteristics such as the moving speed of flotation foam can be accurately obtained in real time,it can provide a basis for the optimization and adjustment of control parameters such as liquid level,charging amount and aeration amount in the flotation process.In order to obtain the moving speed of flotation foam effectively,a feature extraction method based on improved GMS feature matching algorithm is proposed in this paper.Firstly,the ORB algorithm is used to extract and describe the foam feature points,and then the GMS feature matching algorithm is used to complete the fast matching of feature point pairs.On the basis of the above,the RANSAC algorithm is used to eliminate the false matching points in the feature matching results.Finally,the foam moving speed is obtained by calculating the displacement of the foam feature points.The application test of the collected industrial image data shows that the proposed algorithm not only solves the problem that there are many false matching points in the flotation foam image feature extraction of traditional algorithm,but also effectively improves the efficiency and stability of flotation foam feature extraction.

Key words: Flotation foam image, ORB algorithm, GMS feature matching, RANSAC algorithm, Foam movement velocity extraction

中图分类号:

TP391

刘惠中, 余华富, 彭志龙. 基于改进GMS特征匹配算法的浮选泡沫移动速度特征提取[J]. 计算机科学, 2022, 49(11A): 211000064-6. https://doi.org/10.11896/jsjkx.211000064

LIU Hui-zhong, YU Hua-fu, PENG Zhi-long. Feature Extraction of Flotation Foam Moving Speed Based on Improved GMS Feature Matching Algorithm[J]. Computer Science, 2022, 49(11A): 211000064-6. https://doi.org/10.11896/jsjkx.211000064

参考文献

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基于改进GMS特征匹配算法的浮选泡沫移动速度特征提取

Feature Extraction of Flotation Foam Moving Speed Based on Improved GMS Feature Matching Algorithm

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