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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

John P. Chiverton

Olubisi Ige

Stephanie J. Barnett

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TONY PARRY tony.parry@nottingham.ac.uk
Associate Professor



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, 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
DOI https://doi.org/10.1109/TIP.2017.2722234
Public URL http://eprints.nottingham.ac.uk/id/eprint/44003
Publisher URL http://ieeexplore.ieee.org/document/7964702/
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
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.

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf



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