Multiscale Shannon’s entropy modelling of orientation and distance in steel fiber micro-tomography data

John Chiverton, Olubisi Ige, Stephanie Barnett, Tony Parry

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This work is concerned with the modelling and analysis of the orientation and distance between steel fibers in Xray 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.
Original languageEnglish
Pages (from-to)5284-5297
JournalIEEE Transactions on Image Processing
Issue number11
Publication statusPublished - 30 Jun 2017


  • information theory
  • Image Processing
  • micro-CT
  • Steel Fibre
  • 3D imaging
  • 3D tomography
  • entropy
  • steel
  • tensile stress
  • antisotropic magnetoresistance
  • eigenvalues and eigenfunctions
  • data models
  • concrete


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