Abstract
The determination of the gray threshold is crucial for the quantitative characterization of digital images. In this study, a new algorithm is proposed to determine the optimal image segmentation threshold. This algorithm is based on a combined analysis of the gray distribution curve and its second differential distribution curve of the digital image. Then, the feasibility and accuracy of the Liu–Cao algorithm are compared with the other 16 algorithms and verified by mercury injection method (MIP) results. Results show that the proposed segmentation threshold algorithm can effectively segment the digital images obtained by various imaging techniques (SEM, CT, FIB/SEM, etc.) and can accurately extract the pore (crack) structures from the image. Image filtering has a certain influence on the gray threshold determination and quantitative characterization, and the impact depends on the quality of the original image. This algorithm can be easily understood and mastered by the researchers and can be widely used in geotechnical and geological areas.
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Acknowledgements
The authors are grateful to the support of the National Natural Science Foundation of China (No. 51809263), the Fundamental Research Funds for the Central Universities (China University of Mining and Technology) (2019ZDPY13), and China Postdoctoral Science Foundation (2019M661993).
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Liu, JF., Cao, XL., Xu, J. et al. A new method for threshold determination of gray image. Geomech. Geophys. Geo-energ. Geo-resour. 6, 72 (2020). https://doi.org/10.1007/s40948-020-00198-2
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DOI: https://doi.org/10.1007/s40948-020-00198-2