Individual Yarn Fibre Extraction from Micro CT: Multilevel Machine Learning Approach [post]

Petr Henys, Lukáš Čapek
2020 unpublished
The internal structure and mechanics of the fibre materials, such as yarn or woven textile, are highly complex. Exploring the fibre structure is an essential step in material engineering either from the experimental or computational point of view. In this study, a new method to extract geometrical and morphological parameters of fibre structures is proposed. The method benefits from standard image analysis and machine learning technique to efficiently extract fibre segments from microcomputer
more » ... mography data. The proposed algorithm is tested on the yarn and woven textile materials with different resolution and quality. The developed method can extract the individual fibres with varying accuracy from 73-100% with processing time 2-5s on the tested samples.
doi:10.31224/osf.io/m4fjr fatcat:hlng3xql2vhi7aseocr3i5ij2y