John P. Chiverton
Multiscale Shannon’s entropy modelling of orientation and distance in steel fiber Micro-Tomography data
Chiverton, John P.; Ige, Olubisi; Barnett, Stephanie J.; Parry, Tony
Authors
Olubisi Ige
Stephanie J. Barnett
Tony Parry
Abstract
This work is concerned with the modelling and analysis of the orientation and distance between steel fibers in X-ray Micro-Tomography (XCT) data. The advantage of combining both orientation and separation in a model is that it helps provide a detailed understanding of how the steel fibers are arranged, which is easy to compare. The developed models are designed to summarise the randomness of the orientation distribution of the steel fibers both locally and across an entire volume based on multiscale entropy. Theoretical modelling, simulation and application to real imaging data are shown here. The theoretical modelling of multiscale entropy for orientation includes a proof showing the final form of the multiscale taken over a linear range of scales. A series of image processing operations are also included to overcome interslice connectivity issues to help derive the statistical descriptions of the orientation distributions of the steel fibers. The results demonstrate that multiscale entropy provides unique insights into both simulated and real imaging data of steel fiber reinforced concrete.
Citation
Chiverton, J. P., Ige, O., Barnett, S. J., & Parry, T. (2017). Multiscale Shannon’s entropy modelling of orientation and distance in steel fiber Micro-Tomography data. IEEE Transactions on Image Processing, 26(11), 5284-5297. https://doi.org/10.1109/TIP.2017.2722234
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 2, 2017 |
Publication Date | Jun 30, 2017 |
Deposit Date | Jul 5, 2017 |
Publicly Available Date | Jul 5, 2017 |
Journal | IEEE Transactions on Image Processing |
Print ISSN | 1057-7149 |
Electronic ISSN | 1941-0042 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 26 |
Issue | 11 |
Pages | 5284-5297 |
DOI | https://doi.org/10.1109/TIP.2017.2722234 |
Public URL | https://nottingham-repository.worktribe.com/output/870214 |
Publisher URL | http://ieeexplore.ieee.org/document/7964702/ |
Additional Information | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Contract Date | Jul 5, 2017 |
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