Evaluation of Visual Based Aggregate Shape Classifications Using the University of Illinois Aggregate Image Analyzer (UIAIA)

摘要

Aggregate physical shape or morphology affects the engineering behavior of both unbound and bound pavement layers. Simple shape classification methods based on visual charts previously developed by geologists are often subjective and qualitative in describing the aggregate physical shape properties. The more recent classification systems based on image analysis are gaining more recognition in effectively describing the different levels of aggregate morphologies by using quantitative shape indices. This paper presents an imaging based evaluation of three commonly known visual charts using the validated aggregate image analysis device, University of Illinois Aggregate Image Analyzer (UIAIA). The evaluations using UIAIA indicates that Rittenhouse's "sphericity" basically measures the aggregate particle overall shape as quantified by the flat and elongated ratio; Krumbein's "angularity" indirectly identifies the aggregate particle combined angularity and surface texture properties; and finally, Lees' "roundness" roughly measures the aggregate angularity, which also measures overall aggregate shape.