Insegt Fibre: A Powerful Segmentation Tool for Quantifying Fibre Architecture in Composites

Monica Jane Emerson; Kristine M. Jespersen; Ying  Wang; Philip J. Withers; Vedrana Andersen Dahl; Knut Conradsen; Lars Pilgaard Mikkelsen; Anders Bjorholm Dahl

Insegt Fibre: A Powerful Segmentation Tool for Quantifying Fibre Architecture in Composites

Monica Jane Emerson
, Kristine M. Jespersen
, Ying Wang
, Philip J. Withers
, Vedrana Andersen Dahl
, Knut Conradsen
, Lars Pilgaard Mikkelsen
, Anders Bjorholm Dahl

University of Manchester

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

Insegt Fibre is a tool for volumetric fibre segmentation, that is appropriate for densely packed fibres. The robustness to image quality of the underlying dictionary-based algorithm has opened up new opportunities for micro-structural characterisation of fibre-reinforced polymers. The recent user-friendly version of the robust fibre-detection algorithm makes image-based characterisation of fibrous materials simpler and more accessible.

Original language	English
Title of host publication	Proceedings of 2019 International Conference on Tomography of Materials & Structures
Number of pages	2
Publication date	2019
Publication status	Published - 2019
Event	2019 International Conference on Tomography of Materials & Structures - Pullman Cairns International, Cairns, Australia Duration: 22 Jul 2019 → 26 Jul 2019 http://ictms2019.org/

Conference

Conference	2019 International Conference on Tomography of Materials & Structures
Location	Pullman Cairns International
Country/Territory	Australia
City	Cairns
Period	22/07/2019 → 26/07/2019
Internet address	http://ictms2019.org/

Keywords

X-ray computed tomography
Image segmentation
Fibre tracking
Fibre orientations

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@inproceedings{ac3583dd0e3741b5b19f8f7fd904c34e,

title = "Insegt Fibre: A Powerful Segmentation Tool for Quantifying Fibre Architecture in Composites",

abstract = "Insegt Fibre is a tool for volumetric fibre segmentation, that is appropriate for densely packed fibres. The robustness to image quality of the underlying dictionary-based algorithm has opened up new opportunities for micro-structural characterisation of fibre-reinforced polymers. The recent user-friendly version of the robust fibre-detection algorithm makes image-based characterisation of fibrous materials simpler and more accessible.",

keywords = "X-ray computed tomography, Image segmentation, Fibre tracking, Fibre orientations",

author = "Emerson, \{Monica Jane\} and Jespersen, \{Kristine M.\} and Ying Wang and Withers, \{Philip J.\} and Dahl, \{Vedrana Andersen\} and Knut Conradsen and Mikkelsen, \{Lars Pilgaard\} and Dahl, \{Anders Bjorholm\}",

year = "2019",

language = "English",

booktitle = "Proceedings of 2019 International Conference on Tomography of Materials \& Structures",

note = "2019 International Conference on Tomography of Materials \& Structures, ICTMS 2019 ; Conference date: 22-07-2019 Through 26-07-2019",

url = "http://ictms2019.org/",

}

Emerson, MJ, Jespersen, KM, Wang, Y, Withers, PJ, Dahl, VA , Conradsen, K , Mikkelsen, LP & Dahl, AB 2019, Insegt Fibre: A Powerful Segmentation Tool for Quantifying Fibre Architecture in Composites. in Proceedings of 2019 International Conference on Tomography of Materials & Structures. 2019 International Conference on Tomography of Materials & Structures, Cairns, Queensland, Australia, 22/07/2019.

TY - GEN

T1 - Insegt Fibre: A Powerful Segmentation Tool for Quantifying Fibre Architecture in Composites

AU - Emerson, Monica Jane

AU - Jespersen, Kristine M.

AU - Wang, Ying

AU - Withers, Philip J.

AU - Dahl, Vedrana Andersen

AU - Conradsen, Knut

AU - Mikkelsen, Lars Pilgaard

AU - Dahl, Anders Bjorholm

PY - 2019

Y1 - 2019

N2 - Insegt Fibre is a tool for volumetric fibre segmentation, that is appropriate for densely packed fibres. The robustness to image quality of the underlying dictionary-based algorithm has opened up new opportunities for micro-structural characterisation of fibre-reinforced polymers. The recent user-friendly version of the robust fibre-detection algorithm makes image-based characterisation of fibrous materials simpler and more accessible.

AB - Insegt Fibre is a tool for volumetric fibre segmentation, that is appropriate for densely packed fibres. The robustness to image quality of the underlying dictionary-based algorithm has opened up new opportunities for micro-structural characterisation of fibre-reinforced polymers. The recent user-friendly version of the robust fibre-detection algorithm makes image-based characterisation of fibrous materials simpler and more accessible.

KW - X-ray computed tomography

KW - Image segmentation

KW - Fibre tracking

KW - Fibre orientations

M3 - Article in proceedings

BT - Proceedings of 2019 International Conference on Tomography of Materials & Structures

T2 - 2019 International Conference on Tomography of Materials & Structures

Y2 - 22 July 2019 through 26 July 2019

ER -

Insegt Fibre: A Powerful Segmentation Tool for Quantifying Fibre Architecture in Composites

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Keywords

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