Digital image color analysis to evaluate moisture sensitivity of hot mix asphalt (HMA) mixes

Abstract

Moisture in hot mix asphalt (HMA) can cause serious damage like cracks and ruts if left untreated. This is due to the separation of binder and aggregates caused by moisture-induced stripping. Existing approaches for assessing moisture damage in asphalt are time-consuming, destructive, and expensive to implement. In contrast, digital image analysis provides a simple, inexpensive, and non-destructive method to identify moisture-sensitive mixes. Color, as an essential characteristic of an image, effectively conveys information about its content. This study seeks to explore the potential of analyzing digital image color in the L a* b* color space to assess the moisture sensitivity of HMA after Moisture Induced Stress Tester (MIST) conditioning. Laboratory compacted specimens of loose asphalt mixtures from the field were studied by image processing followed by statistical test of significance. It is found that the two parameters, namely, ‘average color value for L channel’ and ‘standard deviation value for b* channel’, can be used to distinguish between moisture-sensitive and non-sensitive mixes. The findings of this study suggest that future research may find color to be a helpful criterion for characterizing asphalt materials using digital image processing