Three-dimensional structural imaging of rock components and methods for component segmentation and extraction

The assumption of uniformity traditional in macroscopic studies makes it hard to explain why the distribution of stress fields in rocks with the same macroscopic characteristics but complex compositions and structures is not the same. Research into the mechanical engineering behaviour of engineering rock masses has therefore become focused on quantitative characterisation of internal structure and fracture mechanisms. To determine accurately the composition and microscopic structure of a specimen in three dimensions, the analogue computed tomography (CT) signal from a sample was digitised and the X-ray absorption values (CT values) were converted into a two-dimensional digital matrix; the filtered back-projection algorithm was then used to reconstruct the 3D projection, the non-local means algorithm to correct for beam hardening so as to improve the microstructural boundary resolution, and the improved Otsu algorithm as a basis for segmenting the reconstructed 3D image to extract the geometric morphology and spatial distribution of typical components of the sandsone such as pores, cracks, cement and mineral particles.
The assumption of uniformity traditional in macroscopic studies makes it hard to explain why the distribution of stress fields in rocks with the same macroscopic characteristics but complex compositions and structures is not the same. Research into the mechanical engineering behaviour of engineering rock masses has therefore become focused on quantitative characterisation of internal structure and fracture mechanisms. To determine accurately the composition and microscopic structure of a specimen in three dimensions, the analogue computed tomography (CT) signal from a sample was digitised and the X-ray absorption values (CT values) were converted into a two-dimensional digital matrix; the filtered back-projection algorithm was then used to reconstruct the 3D projection, the non-local means algorithm to correct for beam hardening so as to improve the microstructural boundary resolution, and the improved Otsu algorithm as a basis for segmenting the reconstructed 3D image to extract the geometric morphology and spatial distribution of typical components of the sandsone such as pores, cracks, cement and mineral particles.