以浮选泡沫图像序列为对象,研究浮选泡沫图像序列速度特征提取方法,分析泡沫速度特征与浮选性能间的关系。提出一种抗尺度快速变化和具有旋转不变性的模板匹配算法,利用宏块跟踪技术对浮选泡沫图像序列的泡沫速度特征进行估计,得出像素级的泡沫运动速度参量。然后,采用二维拉格朗日曲面插值方法提取亚像素位移,得出精确的亚像素级位移参量。结果表明:在浮选过程中,减少浮选泡沫运动速度的紊乱程度能减小已粘附在泡沫上的矿物粒子的脱附率,进而提高浮选精矿品位,降低尾矿中有用矿物含量。
Based on the study of the bubble image sequences, the characteristics of the forth velocities were extracted, and the relationship between the froth speed characteristic and the froth flotation performance was discussed. Hence, a new fast template matching algorithm was presented. This algorithm is invariant to arbitrary rotation revolving and scaling, and using macro-block tracking method to calculate the froth motion velocity, the integral pixels velocity characteristic can be obtained; then, the sub-pixels velocity parameters was extracted using the two-dimension Lagrange surface interpolation and the full precise sub-pixel scale froth bubbles motion velocity was gained. The results show that the decrease of froth velocity turbulence degree in the flotation production is able to decrease the detach ratio of the mineral particles on the bubbles and then to improve the concentrate grade and decrease the ratio of minerals in tailings.