Abstract
An intuitive and sparse representation of the void space of porous materials supports the efficient analysis and visualization of interesting qualitative and quantitative parameters of such materials. We introduce definitions of the elements of this void space, here called pore space, based on its distance function, and present methods to extract these elements using the extremal structures of the distance function. The presented methods are implemented by an image-processing pipeline that determines pore centers, pore paths and pore constrictions. These pore space elements build a graph that represents the topology of the pore space in a compact way. The representations we derive from μCT image data of realistic soil specimens enable the computation of many statistical parameters and, thus, provide a basis for further visual analysis and application-specific developments. We introduced parts of our pipeline in previous work. In this chapter, we present additional details and compare our results with the analytic computation of the pore space elements for a sphere packing in order to show the correctness of our graph computation.
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Acknowledgements
This work was partly funded by the German Research Foundation (DFG) in the project “Conditions of suffosive erosion phenomena in soil”. Special thanks go to Norbert Lindow for providing his implementation of the Voronoi graph algorithm.
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Homberg, U., Baum, D., Wiebel, A., Prohaska, S., Hege, HC. (2014). Definition, Extraction, and Validation of Pore Structures in Porous Materials. In: Bremer, PT., Hotz, I., Pascucci, V., Peikert, R. (eds) Topological Methods in Data Analysis and Visualization III. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-04099-8_15
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DOI: https://doi.org/10.1007/978-3-319-04099-8_15
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