Aggregate is the most widely used pavement surface materials. It has long been recognized that the particle size distribution and morphological properties can significantly influence the skeleton or structure of an aggregate mixture, thus making a great impact on the performance of pavement system. However, traditional methods for determining the aggregate index properties are time-consuming and usually cannot provide quantitate evaluations on particle shapes. With the advance in computing power and image analysis techniques, new algorithms and equipment have been developed to characterize the aggregate index properties. This paper provides a review on the most promising computer vision technology. Discussions on shortcomings of the methods and recommendations for future research are also provided.

CICTP