Title
Orientation-guided two-scale approach for the segmentation and quantitative description of woven bundles of fibers from three-dimensional tomographic images
Abstract
This paper proposes a two-scale approach for the description of fibrous materials from tomographic data. It operates at two scales: coarse scale to describe weaving patterns and fine scale to depict fiber layout within yarns. At both scales, the proposed approach starts with the segmentation of yarns and fibers. Then, the fibrous structure (fiber diameters, fiber and yarn orientations, fiber density within yarns) is described. The segmentation algorithms are applied to a chunk of a woven ceramic-matrix composite observed at yarn and fiber scales using tomographic data from the European synchrotron radiation facility. The fiber and yarn segmentation results allow investigation of intrayarn fiber layout. The analysis of intrayarn fiber density and orientations shows the effects of the weaving process on fiber organization, in particular fiber compaction or yarn shearing. These results pave the way toward a deeper analysis of such materials. Indeed, the data collected with the proposed methods are a key starting point for realistic image synthesis. Such images may in turn be used to validate the fiber and yarn segmentation algorithms. Besides, and above all, they will allow material behavior simulation, aiming at the evaluation of the material's strengths and weaknesses inferred from its fibrous architecture. (C) 2015 SPIE and IS&T
Year
DOI
Venue
2015
10.1117/1.JEI.24.6.061113
JOURNAL OF ELECTRONIC IMAGING
Keywords
Field
DocType
three-dimensional texture,image analysis,orientation,fibrous composite,tomography
Computer vision,Weaving,Yarn,Fiber,Shearing (physics),Computer science,Segmentation,Tomography,Image segmentation,Image synthesis,Artificial intelligence
Journal
Volume
Issue
ISSN
24
6
1017-9909
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
cedric chapoullie100.34
Jean Pierre Da Costa2667.09
michel cataldi300.34
Gérard L. Vignoles400.68
Christian Germain511318.95