Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites

Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites

The purpose of this work is to find an effective image segmentation method for lab-based micro-tomography (µ-CT) data of carbon fiber reinforced polymers (CFRP) with insufficient contrast-to-noise ratio. The segmentation is the first step in creating a realistic geometry (based on &#181...

Full description

Bibliographic Details
Main Authors: Yuriy Sinchuk, Pierre Kibleur, Jan Aelterman, Matthieu N. Boone, Wim Van Paepegem
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Materials
Subjects:
fabrics/textiles
carbon-fiber reinforced polymer
multi-scale modelling
image segmentation
microcomputed tomography
Online Access:https://www.mdpi.com/1996-1944/13/4/936

Internet

https://www.mdpi.com/1996-1944/13/4/936

Similar Items