Analyzing Aggregate Size Distribution of Asphalt Mixtures Using Simple 2D Digital Image Processing Techniques View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-02-18

AUTHORS

Ki Hoon Moon, Augusto Cannone Falchetto, Michael P. Wistuba, Jin Hoon Jeong

ABSTRACT

In this paper, a simple two-dimensional Digital Image Processing (DIP) technique was used to obtain aggregate gradation curves for a set of 28 asphalt mixtures prepared with different asphalt binders and air void contents, aggregates 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 prepared 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 aggregate 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 distributions curves, which were then graphically and statistically compared to the original mix design of each of the 28 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, relatively poor gradation predictions were observed for aggregates equal or smaller than 2.38 mm. More... »

PAGES

1309-1326

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13369-015-1594-0

DOI

http://dx.doi.org/10.1007/s13369-015-1594-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020261307


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