RESTORATION OF TEXTILE YARN DISTORTED LOW-RESOLUTION MICRO COMPUTED TOMOGRAPHY CROSS SECTION IMAGES: A MATLAB RESTORATION ALGORITHM

1,2 ABDELKADER Mohamed
Co-authors:
1 PETRIK Stanislav
Institutions:
1 Department of Advanced Materials, Institute for Nanomaterials, Advanced Technologies, and Innovation (CXI), Technical University of Liberec, Liberec, Czech Republic, EU, mohamed.fawzy@mena.vt.edu
2 Department of Glass producing Machines and Robotics, Faculty of Mechanical Engineering, Technical University of Liberec, Liberec, Czech Republic, EU
Conference:
15th International Conference on Nanomaterials - Research & Application, OREA Congress Hotel Brno, Czech Republic, EU, October 18 - 20, 2023
Proceedings:
Proceedings 15th International Conference on Nanomaterials - Research & Application
Pages:
380-385
ISBN:
978-80-88365-15-0
ISSN:
2694-930X
Published:
13th December 2023
Metrics:
112 views / 56 downloads
Abstract

Textile yarn is a group of twisted fibers with diameters of a few micrometers, requiring a nano-resolution scanner to capture precise details of the single fibers perfectly to make a digital twine of the scanned yarn. Computed tomography (CT) technology can 3D digitally scan the sample and achieve a digital twin. The fine fibers' diameter requires a nano-CT to achieve a high-resolution yarn's digital twin; nano-CTs are more expensive than micro-CTs and require about eight times the scanning time compared to micro-CTs, which means more computational power to reconstruct and analyze the scanned objects. This paper introduces a systematic MATLAB algorithm to regenerate distorted yarn's micro-CT low-resolution cross-section images. The algorithm segments the distorted images' fibers, identifies them, and regenerates the clean, high-resolution fibers. The algorithm performance is compared to the optical microscopic cross-section image measurements using ImageJ. The results revealed that before processing, the mean fiber diameter measured 9.60 ± 0.78 µm, while post-processing it measured 10.33 ± 0.49 µm. Notably, the algorithm effectively decreased the dispersion of fiber diameters around the mean by 40%, maintaining a diameter close to the design diameter of the fibers of 10 µm.

Keywords: Yarn, fibers, micro-computed tomography, cross-section images, MATLAB, algorithms, ImageJ.

© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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