Literature DB >> 32266723

Investigation of cross-sectional image analysis method to determine the blending ratio of polyester/cotton yarn.

S Lu1, B Xin2, N Deng1, L Wang1, W Wang1.   

Abstract

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.
© 2020 Royal Microscopical Society.

Keywords:  Binarisation; blending ratio; edge detection; greyscale inversion; median filtering denoising; roundness algorithm

Year:  2020        PMID: 32266723     DOI: 10.1111/jmi.12892

Source DB:  PubMed          Journal:  J Microsc        ISSN: 0022-2720            Impact factor:   1.758


  1 in total

1.  MATLAB Algorithms for Diameter Measurements of Textile Yarns and Fibers through Image Processing Techniques.

Authors:  Mohamed Abdelkader
Journal:  Materials (Basel)       Date:  2022-02-10       Impact factor: 3.623

  1 in total

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