A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Segmentation of Low‐contrast Three‐phase X‐ray Computed Tomography Images of Porous Media
X‐Ray Computed Tomography (XCT) is an important tool to study porous‐media microstructure and fluids present within the void space. In the presence of multiple fluid phases, the contrast between the fluid phases becomes important for accurate image segmentation. In some cases, it is not possible to illuminate one of the fluid phases. The result is then a single image containing multiple phases that may contain overlapping peaks of the fluid phases due to little difference in the absorption coefficients. Building upon work done in medical‐image‐processing research, we have adopted a nonlinear anisotropic diffusion technique to remove noise from the XCT image that also leads to improved peak separation in the image histogram. The noise‐free image is the then segmented using indicator kriging and the results are compared with segmentation results obtained using absorption‐edge imaging. absorption coefficients; crystal microstructure; image processing; image segmentation; single photon emission computed tomography
Segmentation of Low‐contrast Three‐phase X‐ray Computed Tomography Images of Porous Media
X‐Ray Computed Tomography (XCT) is an important tool to study porous‐media microstructure and fluids present within the void space. In the presence of multiple fluid phases, the contrast between the fluid phases becomes important for accurate image segmentation. In some cases, it is not possible to illuminate one of the fluid phases. The result is then a single image containing multiple phases that may contain overlapping peaks of the fluid phases due to little difference in the absorption coefficients. Building upon work done in medical‐image‐processing research, we have adopted a nonlinear anisotropic diffusion technique to remove noise from the XCT image that also leads to improved peak separation in the image histogram. The noise‐free image is the then segmented using indicator kriging and the results are compared with segmentation results obtained using absorption‐edge imaging. absorption coefficients; crystal microstructure; image processing; image segmentation; single photon emission computed tomography
Segmentation of Low‐contrast Three‐phase X‐ray Computed Tomography Images of Porous Media
Alshibli, Khalid A. (editor) / Reed, Allen H. (editor) / Bhattad, P. (author) / Willson, C. S. (author) / Thompson, K. E. (author)
2010-03-01
8 pages
Article/Chapter (Book)
Electronic Resource
English
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