Local Thickness and Anisotropy Approaches to Characterize Pore Size Distribution of 3D Porous Networks
Martin Y. Chiang, Xianfeng Wang
We have proposed a superseding algorithm approach for image analysis of the pore size distribution (PSD) of porous media. This approach adapts the intrinsic definition of skeletonization for an object representation to the characterization of the PSD, and consequently is independent of the analytical technique.The proposed superseding algorithm was applied to a synthetic 2D and a natural 3D image for extracting PSDs. Also, comparisons of the PSD results were made between the proposed approach and the chord-length distribution approach, which has been a tool in the characterization of porous and composite media. Our study indicates that the proposed algorithm is reliable and efficient to evaluate the pore size distribution including local details for porous media with complicated morphologies of any scale. In addition, the skeleton which results during the superseding process can be used to obtain geometrical and morphological characteristics in many other applications.
and Wang, X.
Local Thickness and Anisotropy Approaches to Characterize Pore Size Distribution of 3D Porous Networks, Tissue Engineering, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=852504
(Accessed November 29, 2023)