Application of Image Processing in Soil Mechanics

Whenever someone digs a hole in the ground or takes a relaxing walk on the beach, they directly interact with the soil. In its basic form, soil consists of solid, water, and air phases. Unlike water and metals, soil is a particulate media, and the relative proportion of the individual phases significantly influences its physical properties. Various studies have analyzed soil using image processing to determine its morphological properties. Research involving the digital processing of X-ray Computed Tomography (X-ray CT) images of soil to retrieve physically meaningful information is gaining recognition. This study investigates two-dimensional X-ray CT images of unsaturated granular media taken at specific locations on the wetting and drying curves of the soil water characteristic curve (SWCC) determined for the granular media. The images are segmented into three distinct phases of the media through image histogram-based thresholding. The porosity, void ratio, and degree of saturation are evaluated by counting the appropriate pixels for each phase and applying calibrations between pixels and physical dimensions

Research on establishing numerical model of geo material based on CT image analysis

Abstract Geotechnical engineering material is a kind of heterogeneous composite material. The stone, mineral, gravel, hole, and crack contained in it have different physical and mechanical properties, and their responses to external forces are very different. For example, stress distribution, crack propagation, and failure mode are closely related to material heterogeneity and microstructure. This paper presents a finite element model method for processing CT images of geotechnical materials by using digital image technology. This paper presents a finite element model method for processing CT images of geotechnical materials by using digital image technology. The theory of digital image processing is applied to geotechnical CT image processing to realize pseudo-color enhancement of CT image, and the histograms of different geotechnical CT numbers are obtained. Canny operator is used to detect the edge of geotechnical CT image, and the binary image of geotechnical microstructure is obtained. According to the color change of pseudo-color enhanced image and CT histogram, the meso-structure and variation of rock and soil can be quantitatively analyzed. The finite element model established by this method can fully consider the heterogeneity of geotechnical materials, especially the effect of void distribution on the mechanical properties of geotechnical materials