Abstract:
Digital Image Processing (DIP) algorithms are often required as a
precursor tomeasure the internal characteristics of pavement structures during X-ray
computed tomography (XRCT) based non-destructive evaluation (NDE) of pavement
materials. The improper use of DIP algorithms can result in the significant underor
over-estimation of internal pavement characteristics, thereby affecting pavement
design and maintenance strategies. Past research studies highlighted the significance
of threshold segmentation algorithms and binarization of greyscale images on the
porosity and permeability characteristics of pervious pavement mixtures. In addition,
the use of a watershed segmentation algorithm was introduced to separate interconnected
pore network structure into multiple pores. However, isolated pores were not
removed in past analyses found in the literature due to a lack of consideration in
using ungrouping algorithm to segregate connected and isolated pores. The main
objective of this study is to select the appropriate DIP algorithms that can be used to
evaluate pervious pavement pore network properties from three-dimensional XRCT
based images. In this paper, a key microstructural pore parameter was investigated
using various DIP algorithms for different pervious pavement mixtures and recommendations
are made. It is expected that the results presented in this paper can help
researchers understand the importance of DIP algorithms on XRCT-based pavement
evaluation studies.
