Improved Image Unevenness Reduction and Thresholding Methods for Effective Asphalt X-Ray CT Image Segmentation

The internal structure of asphalt mixture revealed by X-ray computed tomography (CT) images provides useful information in a variety of civil engineering applications. This paper studied two image processing issues commonly encountered in asphalt X-ray CT images: image intensity unevenness caused by beam hardening effect and unrealistic image segmentation. Inspired by nonuniform illumination correction techniques, a grayscale morphological method is proposed to solve image intensity unevenness. Two modified multilevel thresholding methods are developed to effectively divide the asphalt CT images into three phases - air voids, binder, and aggregates. The comparisons of existing multilevel thresholding methods with the ones developed in this study indicate that the proposed methods provide more consistent, robust, and accurate results. Moreover, the developed thresholding objective functions enable a user to easily adjust thresholds to match visual examination or laboratory test results through modifying a single parameter. The developed methods help improve the analysis of asphalt CT images for various engineering applications.