Several automated devices are commercially available for measuring the gradation of unbound stone aggregates. These computerized machines, which provide a rapid alternative to manual sieving, capture and process two-dimensional digital images of aggregate particles to determine grain size distribution. Five of these automated gradation devices were evaluated for accuracy and performance. Fifteen aggregate test samples, with different size, shape, and mineral characteristics, were used in these tests. To quantify how well the machine results compare with data from standard sieve analyses, the CANWE statistic was developed and used. While the machine data did not match the sieve data exactly, the evaluated devices were found to provide good measures of particle gradation for most samples. These tests also indicate that some machines will give more repeatable results in multiple tests of a given material, while others yield better results when testing different materials. The methodology used in this study is suitable for objectively evaluating the accuracy of other rapid gradation machines for various applications. ICAR Project 503 was undertaken to study rapid, automated methods of determining the grain size distribution of unbound aggregate products. Two technologies were studied in detail: digital image analysis and laser profiling. This report summarizes the evaluation of digital imaging devices, while the second part of the final project report describes the development of a laser scanning device for grading aggregates.