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Proceedings Paper

Statistical segmentation and porosity quantification of 3D x-ray microtomography
Author(s): Daniela Ushizima; Dilworth Parkinson; Peter Nico; Jonathan Ajo-Franklin; Alastair MacDowell; Benjamin Kocar; Wes Bethel; James Sethian
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Paper Abstract

High-resolution x-ray micro-tomography is used for imaging of solid materials at micrometer scale in 3D. Our goal is to implement nondestructive techniques to quantify properties in the interior of solid objects, including information on their 3D geometries, which supports modeling of the fluid dynamics into the pore space of the host object. The micro-tomography data acquisition process generates large data sets that are often difficult to handle with adequate performance when using current standard computing and image processing algorithms. We propose an efficient set of algorithms to filter, segment and extract features from stacks of image slices of porous media. The first step tunes scale parameters to the filtering algorithm, then it reduces artifacts using a fast anisotropic filter applied to the image stack, which smoothes homogeneous regions while preserving borders. Next, the volume is partitioned using statistical region merging, exploiting the intensity similarities of each segment. Finally, we calculate the porosity of the material based on the solid-void ratio. Our contribution is to design a pipeline tailored to deal with large data-files, including a scheme for the user to input image patches for tuning parameters to the datasets. We illustrate our methodology using more than 2,000 micro-tomography image slices from 4 different porous materials, acquired using high-resolution X-ray. Also, we compare our results with standard, yet fast algorithms often used for image segmentation, which includes median filtering and thresholding.

Paper Details

Date Published: 12 September 2011
PDF: 14 pages
Proc. SPIE 8135, Applications of Digital Image Processing XXXIV, 813502 (12 September 2011); doi: 10.1117/12.892809
Show Author Affiliations
Daniela Ushizima, Lawrence Berkeley National Lab. (United States)
Dilworth Parkinson, Lawrence Berkeley National Lab. (United States)
Peter Nico, Lawrence Berkeley National Lab. (United States)
Jonathan Ajo-Franklin, Lawrence Berkeley National Lab. (United States)
Alastair MacDowell, Lawrence Berkeley National Lab. (United States)
Benjamin Kocar, Stanford Univ. (United States)
Wes Bethel, Lawrence Berkeley National Lab. (United States)
James Sethian, Univ. of California, Berkeley (United States)


Published in SPIE Proceedings Vol. 8135:
Applications of Digital Image Processing XXXIV
Andrew G. Tescher, Editor(s)

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