## 3 Digital Image Acquisition, Processing and Modelling Reconstruction
### Digital Image Processing Analysis
In addition, the accurate aggregates' morphological characteristics can be quantified by AIMS. The angularity of the aggregate are varied to allow for changes in the Marshall stability and flexural strength of the aggregate while keeping the texture of the aggregate the same. A linear fit to the parabolic equation yielded the \"optimal angularity\" for basalt and limestone at gradient angles of 3100 and 3137 and the \"optimal sphericity\" for basalt and limestone at sphericity of 0.68 and 0.63. There is a possibility for future studies to consider controlling the shape or angularity of the aggregates to be the same. In turn, the effect of their texture indices on the different properties of the aggregates will be investigated. Good surface texture helps to improve the skid resistance of aggregates. However, surface texture belongs to the sub-microscopic category, which is difficult to determine accurately and is mostly replaced by the friction coefficient [94]. The pavement micro-texture is mainly influenced by the aggregate properties inside the pavement. [PERSON] et al. [95] characterized the surface texture of aggregates by mean profile depth (MPD) and investigated the relationship between pavement skid resistance and aggregate texture characteristics through extensive experiments and analysis of multiple variables. [PERSON] et al. [96] proposed an improved pavement texture image segmentation algorithm to comprehensively evaluate the distribution uniformity of asphalt pavement aggregates. The proposed uniformity index (D) of aggregate distribution based on the number and location of texture structures has a good correlation with the texture depth. Surface textures have mostly been used to study the relationship between aggregates and skid resistance in asphalt paving. For asphalt pavement texture structure distribution features, field-based visual inspection methods are normally used. This approach is subjective and does not provide a satisfactory assessment of the degree of superiority of the texture structure distribution on asphalt pavement surfaces. DIP techniques are constantly being innovated and applied to study the effect of aggregate morphological features on the performance of road aggregates. Nevertheless, it is difficult to represent the spatial distribution of texture features of road aggregates in 2D images. Attempts have been made to apply 2D image processing techniques to explore texture structure distributions. Regrettably, there is no excellent method to date for determining the state of the texture structure distribution on asphalt surfaces. In conclusion, 2D aggregate image measurement methods are widely employed in various aspects such as aggregate morphological characteristics, aggregate movement characteristics, void distribution characteristics, etc. By obtaining images of aggregate particles and processing and analyzing the images, the physical properties of aggregates can be studied. Despite the better efficiency of 2D image processing, nonetheless, the vertical depth of 2D image recognition barely reflects the surface texture and spatial morphological features of the aggregates. Meanwhile, since the mixture is a non-homogeneous spatial structure, the interaction between the aggregates and the 2D planar mechanics issue has a large gap.