基于尺度不变特征变换的浮选泡沫图像动态特性提取方法  

Dynamic characteristic extraction method of flotation froth image based on scale invariant feature transform

作　　者：刘颖[1] 张平[1] 赵珺[1] 吕政[1] 王伟[1] 

机构地区：[1]大连理工大学控制科学与工程学院,辽宁大连116023

出　　处：《控制理论与应用》2016年第6期718-726,共9页Control Theory & Applications

基　　金：国家自然科学基金项目(61304213;61273037;61473056);国家"863"计划(2013AA040703)资助~~

摘　　要：本文以矿物浮选过程为背景,针对浮选泡沫不断运动变化导致泡沫图像动态特性难以提取的问题,提出一种基于尺度不变特征变换(scale invariant feature transform,SIFT)浮选泡沫图像动态特性提取方法.首先,依据浮选泡沫独特的运动特性,提出运动匹配区间的概念,然后依据泡沫速度大小和方向对应分布范围改进SIFT算法匹配条件,在此基础上应用基于速率随机抽样一致(RANSAC)算法进一步剔除误匹配点,最后,根据匹配结果提出一种泡沫崩塌率提取方法.采用浮选现场实际泡沫图像进行验证,实验结果表明本文所提方法能够准确提取浮选泡沫速率、崩塌率等动态特性,有效剔除误匹配,同时降低了计算复杂度,提高了计算实时性.As for the mineral flotation process, a new dynamic characteristic extraction method of flotation froth image based on scale invariant feature transform（SIFT） is proposed in this study, considering the difficulty to detect the dynamic characteristic resulted from continuous movement of flotation froth image. Firstly, a concept of motion matching region based on the unique characteristics of flotation froth is proposed, then according to the distribution range of magnitude and direction of bubble velocity to improve SIFT algorithm＇s matching conditions and using random sample consensus（RANSAC） to further eliminate the mismatching. Finally, a new method of extracting the collapse rate of the froth is proposed based on the matching result. Verifying by flotation bubble real images on industrial scene, experimental results show the method proposed in the paper can accurately extract the dynamic characteristics of flotation froth, such as velocity,collapse rate, etc, and effectively eliminate the mismatching while reducing the computational complexity, improving the real-time.

关 键 词：尺度不变特征变换 动态特性 随机抽样一致 误匹配 浮选泡沫图像 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]