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Authors: Khan, F.
Enzmann, Frieder
Kersten, Michael
Title: Beam-hardening correction by a surface fitting and phase classification by a least square support vector machine approach for tomography images of geological samples
Online publication date: 12-Jul-2022
Language: english
Abstract: In X-ray computed microtomography (μXCT) image processing is the most important operation prior to image analysis. Such processing mainly involves artefact reduction and image segmentation. We propose a new two-stage post-reconstruction procedure of an image of a geological rock core obtained by polychromatic cone-beam μXCT technology. In the first stage, the beam-hardening (BH) is removed applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. The final BH-corrected image is extracted from the residual data, or the difference between the surface elevation values and the original grey-scale values. For the second stage, we propose using a least square support vector machine (a non-linear classifier algorithm) to segment the BH-corrected data as a pixel-based multi-classification task. A combination of the two approaches was used to classify a complex multi-mineral rock sample. The Matlab code for this approach is provided in the Appendix. A minor drawback is that the proposed segmentation algorithm may become computationally demanding in the case of a high dimensional training data set.
DDC: 550 Geowissenschaften
550 Earth sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 09 Chemie, Pharmazie u. Geowissensch.
Place: Mainz
Version: Published version
Publication type: Zeitschriftenaufsatz
License: CC BY
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Journal: Solid earth discussions
Pages or article number: 3383
Publisher: Copernicus Publ.
Publisher place: Göttingen
Issue date: 2015
ISSN: 1869-9537
Publisher URL:
Publisher DOI: 10.5194/sed-7-3383-2015
Appears in collections:DFG-OA-Publizieren (2012 - 2017)

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