基于WCGAN的矿物浮选泡沫图像光照不变颜色提取  

WCGAN-based Illumination-invariant Color Measuring of Mineral Flotation Froth Images

作　　者：刘金平 何捷舟 唐朝晖[2] 谢永芳[2] 马天雨 LIU Jin-Ping;HE Jie-Zhou;TANG Zhao-Hui;XIE Yong-Fang;MA Tian-Yu(Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing,Hunan Normal University,Changsha 410081;School of Automation,Central South University,Changsha 410083;School of Physics and Electronics,Hunan Normal University,Changsha 410081)

机构地区：[1]湖南师范大学智能计算与语言信息处理湖南省重点实验室,长沙410081 [2]中南大学自动化学院,长沙410083 [3]湖南师范大学物理与电子科学学院,长沙410081

出　　处：《自动化学报》2022年第9期2301-2315,共15页Acta Automatica Sinica

基　　金：国家自然科学基金(61971188,61771492);国家杰出青年科学基金(61725306);国家自然科学基金-广东联合基金重点项目(U1701261);湖南省自然科学基金(2018JJ3349);湖南省研究生科研创新项目(CX2018B312,CX20190415)资助。

摘　　要：浮选泡沫表面颜色是选矿生产指标(精矿品位)最为快速便捷的直接指示器.然而,泡沫图像信号因受多种可变光照的交叉干扰而不可避免存在严重色偏,导致浮选指标难以准确评估.本文将传统的基于光照估计的图像颜色恒常问题转换为一种结构保持的图到图颜色(风格)转移问题,提出一种基于Wasserstein距离的循环生成对抗网络(Wasserstein distance-based cycle generative adversarial network,WCGAN)用于泡沫图像光照不变颜色特征在线监测.在标准颜色恒常数据集和实际的工业铝土矿浮选过程进行实验验证,结果表明,WCGAN能有效实现各种未知光照条件下(色偏)图像到基准光照条件下的颜色转换,转换速度快且具有模型在线更新功能.与传统的基于生成对抗学习的颜色转换模型相比,WCGAN能更好地保持泡沫图像的轮廓和表面纹理等结构信息,为基于机器视觉的矿物浮选过程生产指标的在线监测提供了有效的客观评价信息.The surface color of flotation froth can be referred as an instant and direct production index(e.g.,concentrate grade)of mineral flotation process.However,serious color deviations will inevitably exist in the collected froth images,due to the adverse interference of varying multi-source illuminations,resulting in great difficulties in achieving accurate evaluation results of production indexes.This paper formulates the illumination estimation task in traditional color constancy as a structure-preserved image-to-image color translation task.It presents a Wasserstein distance-based cycle generative adversarial network(WCGAN)for the illumination-invariant froth color feature measuring.Extensive validation and comparative experiments on benchmark color constancy datasets and an industrial flotation process demonstrate that WCGAN can effectively realize the color translation of froth images from various unknown illuminations to a canonical illumination,which has the merits of fast translation and online model updating.Compared with the traditional generative adversarial networks-based color translation models,WCGAN can maintain the structural features invariance,e.g.,geometric and texture structures,of original images more effectively,providing effective and objective evaluation information for the on-line monitoring of production indices of mineral flotation process.

关 键 词：浮选泡沫图像 循环生成对抗网络 光照不变颜色特征 Wasserstein距离 结构保持 

分 类 号：TD923[矿业工程—选矿] TP391.41[自动化与计算机技术—计算机应用技术]