SYMPOSIA PAPER Published: 01 January 2001

Image Analysis Techniques to Determine Fine Aggregate Angularity


The validity of the Superpave fine aggregate angularity (FAA) test isquestioned by the paving industry. State agencies are concerned that local materials which have provided good field performance now cannot meet the Superpave requirements. Previous research has shown that these questions and concern are valid. The objectives of this study are to evaluate the ability of FAA test procedure to distinguish aggregates with good and poor performance in HMA and to examine the potential of image analysis methods of quantifying fine aggregate angularity.

Twenty-three fine aggregates from different parts of the USA were tested using ASTM C 1252, Method A. These same aggregates were tested using three different image analysis methods, including: Hough transform at University of Arkansas at Little Rock, unified image analysis at Washington State University, and VDG-40 videograder at Virginia Transportation Research Council. Results from the image analysis methods were compared with FAA test results and available pavement performance history.

The FAA test method does not consistently identify angular, cubical aggregates as high quality materials. Reasonably good correlations were found between FAA and all three image analysis methods. Moreover, the image analysis methods exhibited good correlations among themselves. Those crushed cubical fine aggregates with FAA values lower than 45 showed high angularity in all three imaging methods. These crushed, cubical materials also demonstrated good field performance history.

Image analyses appear to be very promising methods for directly measuring fine aggregate angularity and to replace the current FAA method. Since they are in their initial stage, more research work is needed to optimize their use and make them commercially viable

Author Information

Chowdhury, A
Texas Transportation Institute, Texas A&M University, College Station, TX
Button, JW
Texas Transportation Institute, Texas A&M University, College Station, TX
Wilson, D
Graduate Institute of Technology, University of Arkansas at Little Rock, Little Rock, AR
Masad, E
Washington State University, Pullman, WA
Prowell, BD
Virginia Transportation Research Council, Charlottesville, VA
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Developed by Committee: D04
Pages: 128–143
DOI: 10.1520/STP10804S
ISBN-EB: 978-0-8031-5457-5
ISBN-13: 978-0-8031-2892-7