Application of highlight removal and multivariate image analysis to color measurement of flotation bubble images

Application of highlight removal and multivariate image analysis to color measurement of flotation bubble images
复制标题

高光去除和多元图像分析在浮选气泡图像颜色测量中的应用

DOI:
10.1002/ima.20208
复制
发表时间:
2009-12
影响因子:
3.3
通讯作者:
Gui, Weihua
Gui, Weihua
中科院分区:
计算机科学4区
文献类型:
--
作者:
Zhou, Kaijun;Xu, Canhui;Yang, Chunhua;Gui, Weihua

文献摘要

参考文献

被引文献

相似文献

基于机器视觉的分析为泡沫浮选监测提供了一种新技术。收集到的泡沫图像的特征是在不同的照明下,气泡的大小和形状都是不同的。凸泡会导致白色斑点的形成,严重影响泡沫颜色的测量。本文对镜面高光进行检测和预处理,以估计白点区域的底色。由于认为颜色信息与浮选性能有关,因此,在高光涂装应用后,提出了多变量图像分析提取颜色特征,并通过正交最小二乘回归模型进一步提取与矿物品位相关的颜色特征。所建立的关系为预测矿物品位提供了一个有前景的经验模型,而矿物品位是浮选性能的重要指标。实验结果表明,与传统方法相比,该算法可以实现鲁棒性的颜色测量和有效的矿物浓度预测。©2009 Wiley期刊公司光学精密工程学报,2016,33 (2):444 - 444
Machine vision based analysis provides a novel technology for froth flotation monitoring. Froth images collected are characterized by fully occupied bubbles with different size and shape under various illuminations. Convex bubbles lead to the formation of white spots that seriously affect froth color measurement. In this article, specular highlights are detected and preprocessed so as to estimate underlying color of white spots region. Because of the fact that color information is believed to be related to flotation performance, therefore, after the application of highlight inpainting, multivariate image analysis is proposed to extract color features, which are further related to mineral grades by a orthogonal least square regression model. The established relationship provides a promising empirical model to predict mineral grade, which is a significant indicator for flotation performance. Experimental results show that, when compared with traditional methods, the proposed algorithm can achieve a robust color measurement and predict mineral concentration effectively. © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 316–322, 2009
DOI: --
发表时间: 1987
影响因子: 2.1
作者:
G. Klinker;S. Shafer;T. Kanade;Schenley Park
通讯作者: G. Klinker;S. Shafer;T. Kanade;Schenley Park
DOI: 10.1007/bf00137441
发表时间: 1990-01-01
影响因子: 19.5
作者:
KLINKER, GJ;SHAFER, SA;KANADE, T
通讯作者: KANADE, T
DOI: 10.1016/s0892-6875(97)00040-x
发表时间: 1997-06-01
影响因子: 4.8
作者:
Hargrave, JM;Hall, ST
通讯作者: Hall, ST
DOI: 10.1016/j.imavis.2005.12.008
发表时间: 2007
期刊: Image Vis. Comput.
影响因子: --
作者:
C. Barcelos;M. A. Batista
通讯作者: C. Barcelos;M. A. Batista
DOI: 10.1016/j.mineng.2008.03.018
发表时间: 2009
影响因子: 4.8
作者:
J. Reddick;A. Hesketh;Sameer H. Morar;D. Bradshaw
通讯作者: J. Reddick;A. Hesketh;Sameer H. Morar;D. Bradshaw