Premium
Investigation of cross‐sectional image analysis method to determine the blending ratio of polyester/cotton yarn
Author(s) -
LU S.,
XIN B.,
DENG N.,
WANG L.,
WANG W.
Publication year - 2020
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12892
Subject(s) - roundness (object) , yarn , polyester , materials science , textile , digital image , computer science , image processing , digital microscope , preprocessor , microscope , composite material , artificial intelligence , image (mathematics) , optics , physics
Summary It has been considered as a great challenge to identify the blending ratio of polyester/cotton yarn in the field of textile industry. A new digital cross‐sectional image processing method based on geometrical shape analysis is proposed to improve the measurement accuracy of polyester/cotton blend ratio. A self‐developed microscope image capturing system is established to digitalise the cross‐sectional images of polyester/cotton blended yarn. One set of image preprocessing algorithm is developed to conduct greyscale inversion, median filtering denoising and binarisation. The specially designed edge detection algorithm is used to identify the continuous profile of fibres. Finally, the roundness value of the cross‐sectional fibre is calculated based on the proposed roundness algorithm, it can be used to identify the polyester/cotton fibres and calculate the blending ratio of them. Our experimental results show that the new digital analysis method proposed in this paper is feasible for the measurement of polyester/cotton blended ratio; therefore, it has a good application prospect in the field of textile quality control, including the development of new equipment, methods and standards.