基于帧差法和Mean Shift融合的浮选中颗粒跟踪方法

A Particle Tracking Method in Flotation Based on the Frame Difference Method Combined with Mean Shift

为了准确地跟踪浮选视频序列中的絮体颗粒,提出一种结合帧差法与Mean Shift的多运动目标跟踪方法。首先使用帧间差分法对视频文件中的初始两帧图像进行差分处理,进而检测得到运动目标,并确定跟踪窗口和跟踪目标的中心位置;然后结合数学形态学处理优化差分图像,滤除噪声干扰;最后利用求得的核直方图模型在下一帧图像内进行搜索,通过Mean Shift算法找到最佳匹配区域,达到对颗粒位置跟踪的目的。结果表明,该算法可以迅速并高效地跟踪浮选过程中的多个絮体颗粒,具有优越的鲁棒性和实时性。

In order to track floc particles in a flotation video sequence accurately,the paper proposes a multiple movingobject tracking method based on frame difference method and Mean Shift algorithm.First of all,the frame differencemethod is used to process the two adjacent frames in the video sequence,so as to detect the moving object.Then,differentialimages are optimized combined with the mathematical morphology processing method,which is convenient to eliminatenoise interference.Finally,the obtained kernel histogram model is applied to search in the next frame of the video,and theMean Shift algorithm is adopted to find the best matching area,which achieves the particle's position tracking.The resultindicates that this algorithm can track multiple floc particles quickly and efficiently,with excellent robustness and real-timeperformance.