CobWeb 1.0: Machine Learning Tool Box for Tomographic Imaging
Creators
- 1. Institute for Geosciences, Johannes Gutenberg-University, Mainz 55099, Germany
- 2. igem – Institute for Geothermal Resource Management, Berlinstr. 107a, Bingen 55411, Germany
- 3. Federal Institute for Geosciences and Natural Resources (BGR), Hannover 30655, Germany
- 4. APS Antriebs-, Prüf- und Steuertechnik GmbH, Götzenbreite 12, Göttingen-Rosdorf 37124, Germany
- 5. Institute of Applied Geosciences, University of Technology, Darmstadt 64287, Germany
Description
CobWeb toolbox is build for automated image segmentation of X-ray computed tomographic images of geo-materials and thereafter calculation of geometrical parameters such as porosity, pore size distribution and volume fraction.
CobWeb uses unsupervised and supervised machine learning techniques for image segmentation and different image filteration techniques for image prepocessing and noise reduction. For more details please refer to the papers below.
Chauhan, S., Rühaak, W., Khan, F., Enzmann, F., Mielke, P., Kersten, M., Sass, I.: Processing of rock core microtomography images: Using seven different machine learning algorithms, Computers & Geosciences, 86, 120-128, 2016a.
Chauhan, S., Rühaak, W., Anbergen, H., Kabdenov, A., Freise, M., Wille, T., Sass, I.“Phase Segmentation of X-Ray Computer Tomography Rock Images using Machine Learning Techniques: an Accuracy and Performance Study. ” Solid Earth Discuss., se-2016-44, 2016b.
Files
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Additional details
References
- Chauhan, S., Rühaak, W., Khan, F., Enzmann, F., Mielke, P., Kersten, M., Sass, I.: Processing of rock core microtomography images: Using seven different machine learning algorithms, Computers & Geosciences, 86, 120-128, 2016a.
- Chauhan, S., Rühaak, W., Anbergen, H., Kabdenov, A., Freise, M., Wille, T., Sass, I."Phase Segmentation of X-Ray Computer Tomography Rock Images using Machine Learning Techniques: an Accuracy and Performance Study. " Solid Earth Discuss., se-2016-44, 2016b