3D Voxel-Based Approach to Quantify Aggregate Angularity and Surface Texture

Abstract

Angularity and surface texture of aggregate particles are important morphological characteristics and have great influences on the performance of asphalt mix. Several approaches have been developed to characterize the angularity and surface texture of aggregate particles in the past decade. Most existing techniques are limited to the two-dimensional (2D) scheme. In this study, a three-dimensional (3D) approach is proposed to determine the angularity index (AI) and surface texture index (STI) of aggregates, namely the 3D Sobel-Feldman operation, which has not been well used in civil engineering. First, aggregate particles are subjected to X-ray scanning to obtain cross-sectional images, which are then processed and stacked to construct the 3D voxel-based images. Then the gradient vector of each voxel on the surfaces is calculated based on the 3D Sobel-Feldman operation, which was derived and verified in this study based on the 2D Sobel-Feldman operation. The results showed that the 3D Sobel-Feldman operation derived in this study is correct and feasible to be used to determine the 3D AI of aggregates. The AI is determined by the accumulative change of gradient vectors of some selected surface voxels. A pretreatment (dilation followed by erosion) is used to reduce the effect of surface texture on the AI calculation. The surface texture index is determined by the relative loss of voxels after a morphological opening (erosion followed by dilation) operation on the 3D image. User-written coding was used to deal with the massive calculation. A total of 15 aggregate particles were used as case study to investigate the feasibility of the proposed approach to measure the 3D AI and STI. Some factors that affect the AI and STI values were also discussed to find the optimum approach. The 3D STI results were also compared to the 2D results to justify the benefits of the 3D approach.