The loose accumulation CAUSED by landslide, collapse, debris flow, and mine blasting, exerts considerable negative influence to human activities. Besides, it can easily trigger secondary disaster under inner and outer geological conditions. Extraction and measurement of the particle of loose accumulation is of importance for prediction of slope stability and mine blasting. In this paper, the 3D laser scanning is utilized to collect the point clouds of granular materials in physical model (three types of materials) and landslide accumulation in field, respectively. Then, the alpha shapes (AS) and hill climbing-region growing (HC-RG) algorithms are introduced for identifying particles and finding their dimensions (e.g., particle number and radii). Comparison between the recognition results and reality shows that both algorithms can provide a good performance in laboratory physical model, and acceptable results can be obtained when applying two algorithm to field survey. AS algorithm needs less time to process data than HC-GR algorithm; however, the recognition from HC-RG algorithm is more accurate than that by AS algorithm.
Keywords: alpha shapes (AS) algorithm; hill climbing-region growing (HC-RG) algorithm; laser scanning; loose accumulation; particle size measurement.