## 3 Results and Discussion  
### Aggregate Properties  
#### 3.1.1 Morphology Characterization  
In Figure 3, SEM images of diabase, granite, basalt, and type A and type B limestone are displayed. Figure 3 shows the morphologies of the five aggregate particles through a 2.36 mm sieve with \(500\times\) magnification. This microstructure indicates that the shape of the aggregate profile on the aggregate surface is irregular and not uniformly distributed. This may lead to a different adhesion strength at the asphalt binder--aggregate system interface. At the same time, the asphalt binder film will be most likely to spall from the non-textured parts of the aggregate surface under adverse factors such as loading and flooding.  
Figure 3: SEM results of (**a**) type A limestone; (**b**) type B limestone; (**c**) diabase; (**d**) granite; (**e**) basalt.  
Figure 2: Random forest analysis diagram.  
The SEM image needs to be binarized in order to acquire the aggregate surface's textural features with accuracy. The grayscale values of the pixel points on the image were set to 0 or 255, thus presenting the whole image with a distinct visual effect of only black and white. To achieve this process, binarization was performed by ImageJ V1.8.0.112 software, and the processed image is shown in Figure 4. After binarization of the SEM images of the five aggregates, it can be found that the variability of micro-texture shapes and other shapes on the surface of the aggregates is large and extremely irregular. In addition, it can be guessed that the morphological characteristics must cause the bonding ability between the asphalt binder and the aggregates, so the microscopic morphological indicators need to be analyzed.  
First, the Fractal count function in the ImageJ software was used to calculate the microscopic parameters, and two surface morphological indicators, the roughness and shape factor, were selected. The box dimension method was used to determine the fractal dimension of the binarized picture of the aggregate surface texture. The ImageJ software offers a variety of methods for doing this. It can be seen from Figure 5 that the roughness and shape factors of the five aggregates calculated by the ImageJ software do not differ much. The ranking of the fractal dimension of the surface texture of the five aggregates is: type B limestone, granite, type A limestone, diabase, and basalt. Type B limestone aggregate samples have the most developed surface texture, which is conducive to enhancing the bond between asphalt binder and aggregate when other conditions are the same. In addition, the fractal dimension of granite is larger than that of diabase and basalt and similar to that of limestone. This indicates that the surface roughness of the aggregates in this study is not directly related to their lithology. Secondly, the results of the fractal dimension calculation are related to the fractal dimension calculation method, and different results are obtained by different fractal dimension methods. Therefore, the same selection area and threshold selection method should be employed when using ImageJ software.  
Figure 4: Surface morphology binarization results of (**a**) type A limestone; (**b**) type B limestone; (**c**) diabase; (**d**) granite; (**e**) basalt.