Arab J Sci Eng DOI 10.1007/s13369-015-1594-0 RESEARCH ARTICLE - CIVIL ENGINEERING Analyzing Aggregate Size Distribution of Asphalt Mixtures Using Simple 2D Digital Image Processing Techniques Ki Hoon Moon · Augusto Cannone Falchetto · Michael P. Wistuba · Jin Hoon Jeong Received: 7 April 2014 / Accepted: 4 February 2015 © King Fahd University of Petroleum and Minerals 2015 Abstract In this paper, a simple two-dimensional Digital Image Processing (DIP) technique was used to obtain aggre- gate gradation curves for a set of 28 asphalt mixtures prepared with different asphalt binders and air void contents, aggre- gates having various Nominal Maximum Aggregate Size and three percentages of Reclaimed Asphalt Pavement. As part of a larger project, small asphalt mixture beams having the same size of the Bending Beam Rheometer specimens were pre- pared for images acquisition (Red–Green–Blue: RGB scale). Then, RGB images were converted based on a specific DIP algorithm into binary images, and the area of each aggre- gate particle was computed. Finally, the diameters of the aggregates in the binary image were determined through a simple calculation and used to generate aggregate size dis- tributions curves, which were then graphically and statisti- cally compared to the original mix design of each of the 28 K. H. Moon (B ) Samsung C&T Corporation, 5th Fl., Daeryung Gangnam Tower 826-20, Yeoksam 1-Dong, Gangnam-Gu, 135-935 Seoul, South Korea e-mail: moonx113@umn.edu A. Cannone Falchetto · M. P. Wistuba Department of Architecture, Civil Engineering and Environmental Sciences - Pavement Engineering Centre (ISBS), Technical University of Braunschweig, Beethovenstraße 51 b, 38106 Brunswick, Germany e-mail: canno125@umn.edu M. P. Wistuba e-mail: m.wistuba@tu-bs.de J. H. Jeong Department of Civil Engineering, Inha University, 100 Inha-ro, Nam-gu, 402-751 Incheon, South Korea e-mail: jhj@inha.ac.kr K. H. Moon · A. Cannone Falchetto University of Minnesota, Minneapolis, MN, USA asphalt mixtures considered. Good predictions of aggregate gradation were achieved for particle sizes equal or larger than 4.75 mm. Differences in mix design across mixtures having various aggregate size distributions could be clearly observed and statistically analyzed. Due to image resolution limits, rel- atively poor gradation predictions were observed for aggre- gates equal or smaller than 2.38 mm. Keywords Digital Image Processing (DIP) · Nominal Maximum Aggregate Size (NMAS) · Hot Mix Asphalt (HMA) mixture · Reclaimed Asphalt Pavement (RAP) · Aggregate gradation curve · Statistical analysis 1 Introduction Asphalt mixture is a composite material which contains aggregate of various shapes and sizes randomly distributed in a matrix of asphalt binder. One of the most important fac- tors affecting the mechanical performance of asphalt mixture used for pavement application is the size distribution (or gra- dation) of the aggregate skeleton. Commonly, two testing procedures are used to determine the aggregate gradation of asphalt mixtures prepared in laboratory or obtained from field sections: the extracting–sieving and the burning–sieving methods [1, 2]. However, these test methods present a number of drawbacks: They rely on complicated and time- consum- ing analysis procedures, with potential aggregates damage when reducing specimens in particles and particle clustering (due to the presence of asphalt binder), which results in sieve size curves having limited or poor accuracy [1, 2]. Recently nondestructive analysis methods, based on Dig- ital Image Processing (DIP) techniques, have been imple- mented and adopted by a significant number of engineer- ing areas, including Civil Engineering, due to remarkable 123