Please use this identifier to cite or link to this item:
Authors: Khan, Faisal
Enzmann, Frieder
Kersten, Michael
Title: Multi-phase classification by a least-squares support vector machine approach in tomography images of geological samples
Online publication date: 2-Aug-2016
Year of first publication: 2016
Language: english
Abstract: Image processing of X-ray-computed polychromatic cone-beam micro-tomography (µXCT) data of geological samples mainly involves artefact reduction and phase segmentation. For the former, the main beam-hardening (BH) artefact is removed by 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. A Matlab code for this approach is provided in the Appendix. The final BH-corrected image is extracted from the residual data or from the difference between the surface elevation values and the original grey-scale values. For the segmentation, we propose a novel least-squares support vector machine (LS-SVM, an algorithm for pixelbased multi-phase classification) approach. A receiver operating characteristic (ROC) analysis was performed on BHcorrected and uncorrected samples to show that BH correction is in fact an important prerequisite for accurate multiphase classification. The combination of the two approaches was thus used to classify successfully three different more or less complex multi-phase rock core samples.
DDC: 550 Geowissenschaften
550 Earth sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 09 Chemie, Pharmazie u. Geowissensch.
Place: Mainz
URN: urn:nbn:de:hebis:77-publ-545088
Version: Published version
Publication type: Zeitschriftenaufsatz
License: CC BY
Information on rights of use:
Journal: Solid earth
Pages or article number: 481
Publisher: Copernicus Publ.
Publisher place: Göttingen
Issue date: 2016
ISSN: 1869-9529
Publisher URL:
Publisher DOI: 10.5194/se-7-481-2016
Appears in collections:JGU-Publikationen

Files in This Item:
  File Description SizeFormat
54508.pdf3.78 MBAdobe PDFView/Open