Persistent Identifier
|
doi:10.18419/darus-1847 |
Publication Date
|
2021-07-07 |
Title
| Fracture network segmentation |
Author
| Lee, Dongwon (University of Stuttgart) - ORCID: 0000-0002-5359-7803
Nikolaos, Karadimitriou (University of Stuttgart) - ORCID: 0000-0002-9461-6214
Steeb, Holger (University of Stuttgart) - ORCID: 0000-0001-7602-4920 |
Point of Contact
|
Use email button above to contact.
Steeb, Holger (University of Stuttgart, Institute of Applied Mechanics (CE) & SC SimTech) |
Description
| This dataset contains the codes to reproduce the five different segmentation results of the paper Lee et al (2021). The original dataset before applying these segmentation codes could be found in Ruf & Steeb (2020). The adopted segmentation methods in order to identify the micro fractures within the original dataset are the Local threshold, Sato, Chan-Vese, Random forest and U-net model. The Local threshold, Sato and U-net models are written in Python. The codes require a version above Python 3.7.7 with tensorflow, keras, pandas, scipy, scikit and numpy libraries. The workflow of the Chan-Vese method is interpreted in Matlab2018b. The result of the Random forest method could be reproduced with the uploaded trained model in an open source program ImageJ and trainableWeka library. For further details of operation, please refer to the readme.txt file. |
Subject
| Computer and Information Science; Earth and Environmental Sciences; Engineering |
Keyword
| Micro fractures
Image segmentation https://www.wikidata.org/wiki/Q56933 (Wikidata)
Machine learning https://www.wikidata.org/wiki/Q2539 (Wikidata)
Thermally treated Carrara marble https://www.wikidata.org/wiki/Q40088 (Wikidata) |
Topic Classification
| Software |
Related Publication
| Lee, D., Karadimitriou, N., Ruf, M., & Steeb, H. (2021). Detecting micro fractures with X-ray computed tomography. arXiv: 2103.12821 https://arxiv.org/abs/2103.12821 |
Language
| English |
Producer
| University of Stuttgart (Institute of Applied Mechanics (CE) - Chair for Continuum-Mechanics) https://www.mib.uni-stuttgart.de/en |
Production Date
| 2021 |
Production Location
| University of Stuttgart, Institute of Applied Mechanics (CE), Stuttgart, 70569, Germany |
Funding Information
| DFG: 327154368 |
Project
| SFB 1313 (Level 1)
Project B05 (Level 2) |
Distributor
| University of Stuttgart (Institute of applied mechanics (CE)) |
Distribution Date
| 2021-05-26 |
Depositor
| Lee, Dongwon |
Deposit Date
| 2021-05-11 |
Data Type
| program source code |
Related Dataset
| Ruf, M., & Steeb, H. (2020). micro-XRCT data set of Carrara marble with artificially created crack network: fast cooling down from 600°C. DaRUS. https://doi.org/10.18419/DARUS-682 |
Did it work?
| Yes |
Explanation
| By applying the codes, the micro fractures within tomographic images were able to be successfully extracted. |