A study of the dynamic extraction method for granular flow thickness based on digital image processing

The granular flow thickness and its evolution trend are key factors in analyses of the physical model experiments of avalanches. At present, the measurements of granular flow thickness mainly include sensor monitoring, mechanical measurement and manual measurement. With the development of computer technology, digital image processing methods have been applied in more and more subjects including engineering geology. In this paper, a series of granular chute flow experiments are conducted for the extraction of granular flow thicknesses. Based on the digital image processing methods including adaptive median filter, image binarization, image erosion and seed filling, the granular flow image sequence recorded by the high-speed camera is processed and analysed with related codes compiled, thereby achieving continuous extraction of flow thickness during the granular flow propagation. The results show that the granular flow thicknesses extracted with the digital image processing methods are consistent with the measured true thicknesses in the main bodies of the granular flows. Some deviations appear in the tail of granular flow accompanied by significant particle dispersions. The deviations are mainly attributed to the fact that some particles in the three-dimensional space show overlapping phenomenon in the two-dimensional image, which results in the illusion of granular continuity. In general, the granular flow thicknesses obtained with the digital image processing methods is of a high accuracy in the densely packed granular flows. Compared with other methods, this method is of higher efficiency, higher sampling rate and lower disturbance on granular flows. In addition, additional parameters, such as velocities and displacement, can be obtained simultaneously. Therefore, this method can be used as one of the conventional methods to obtain kinematic parameters in granular flow experiments.