Digital-volume-correlation-assisted crack extraction using X-ray computed tomography images of cementitious materials

The image segmentation results for microcrack detection suffer from poor continuity and integrity due to noise, grayscale inhomogeneity, and the very small size of microcrack voxels. Strain information is introduced to aid crack recognition and reduce the impact of image accuracy on crack detection. A new crack detection method is proposed that combines image processing and digital volume correlation (DVC). This method detects and extracts microcracks with specific propagation directions, distinguishing them from pseudo-cracks. It also enhances the integrity of crack morphology analysis by incorporating both image and mechanical information (DVC) data. Furthermore, analysis of X-ray computed tomography (XCT) images of fractured rubber concrete specimens, along with optical microscope verification, demonstrates that this method is effective for visualizing and quantifying fracture patterns.