Comparison of image segmentation methods in simulated 2D and 3D microtomographic images of soil aggregates

Advances in X-ray microtomography (μCT) are opening new opportunities for examining soil pore structures. However, usefulness of μCT data for pore structure characterization depends on how accurately the grayscale images are segmented into pore and solid components. Multiple segmentation algorithms have been developed; however, one of the difficulties in comparing the accuracy of segmentation algorithms is the lack of ground-truth information in the soil samples subjected to μCT. This means that only the criteria that do not depend on the availability of the ground-truth data can be used in assessing accuracy of the segmentation methods, yet the reliability of such criteria in soil images is unclear. In this study, we simulated 2D and 3D soil images to resolve the problem of the lack of ground-truth information. The objectives of the study were (i) to explore optimal parameter selection for indicator kriging (IK) segmentation; (ii) to compare the accuracy of several commonly used segmentation methods, namely, entropy based method, iterative method, Otsu's method, and IK method; and (iii) to evaluate performance of the region non-uniformity measure (NU), the criterion that does not depend on presence of the ground-truth image, in segmentation method selection for soil images. We found that though there was no single segmentation method that preserved pore characteristics in all the cases, IK method yielded segmented images most similar to the ground-truth in most of the cases when the histogram of image grayscale values had clearly distinguishable peaks. For the image with poorly distinguishable histogram peaks, IK did not perform well, while Otsu's method produced acceptable segmentation results. The results indicated that selecting the segmentation method based on NU did not always produce optimal representation of pore characteristics. However, overall, the NU was found to be an acceptable criterion for segmentation method selection in μCT soil images.

Research highlights
► 2D and 3D soil μCT images, serving as ground-truth information, were simulated.
► Indicator Kriging method yields segmented images most similar to ground-truth images.
► NU is an acceptable criterion for segmentation method selection in μCT soil images.