A volumetrics thresholding algorithm for processing asphalt concrete X-ray CT images

Abstract

This paper presents an automated digital image processing technique for capturing the microstructure of asphalt concrete (AC) from X-ray computed tomography images. It applies to circular cross-section images of AC cores of known volumetrics. Its innovation is that it uses the volumetric properties as the main criterion for establishing grey-level thresholds for the boundaries between air–mastic and mastic–aggregates. The algorithm, implemented in MATLAB™, involves three stages. The first stage involves image pre-processing for contrast enhancement and noise removal. The second stage is the main thresholding routine accepting as input the enhanced images of the first stage and volumetric information for the AC. It consists of two components, namely volumetrics-driven thresholding and 3D representation/sectioning. The third stage further enhances particle separation through edge detection and image segmentation. Examples were provided in imaging actual AC cores of known volumetric properties. The algorithm was shown to produce realistic rendering of the microstructure of ACs. Their quality is suitable for input into numerical simulation.

Keywords:

• asphalt concrete microstructure
• thresholding
• edge detection
• image segmentation
• volumetric

Acknowledgements

Sincere thanks are expressed to Dr Masad of Texas A&M University and to Dr Nazarian of the University of Texas-El Paso for supplying the AC X-ray CT images and the volumetric information, respectively.