Aggregates are the most widely used construction materials in the world in structures built from both asphaltic and portland cement concrete composites. The performance of these composites is affected by aggregate shape characteristics (e.g., angularity, texture, and dimensions). The aggregate imaging system (AIMS) is a computer automated system that was developed to measure aggregate shape characteristics using digital camera images of aggregates. This paper addresses four issues concerning AIMS measurements: (1) enhanced ways of handling and classifying the large data sets typically generated; (2) enhanced automation in processing fine aggregate images that appear to contain touching particles; (3) an improved consideration of measurement variability or repeatability between different operators, different AIMS units, and for aggregate placement and orientation; and (4) comparison of AIMS dimensional measurements with true three-dimensional measurements using X-ray computed tomography on a large coarse aggregate data set. The various aggregate sets used in this study covered a broad range of angularity and texture. The AIMS measurements of the ratios of dimensions were found to have excellent agreement with the more accurate X-ray computed tomography values, but the measurements of the individual dimensions were systematically low by about 10%.