Investigation on Image-Based Digital Method for Identification on Polyester/Cotton Fiber Category 


Vol. 22,  No. 6, pp. 1774-1783, Jun.  2021
10.1007/s12221-021-0802-7


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  Abstract

As of today, it still remains a considerable challenge to identify the polyester/cotton fiber category in the textile industry. Based on shape coefficient analysis, a novel comprehensively-designed and appropriately-developed digital crosssection image processing method was proposed to improve the identification accuracy of polyester/cotton fiber. A selfdeveloped microscope image acquisition system was established, so as to digitalize the cross section of fiber. Aimed at the gray scale enhancement, binarization and opening operation, a set of image preprocessing algorithms was developed. Initially, the edge detection algorithm was used to identify the external contour of the cross-section of fiber. Subsequently, the cross section of fiber was separated by watershed segmentation algorithm, and that, the false fiber was removed by area elimination algorithm. Finally, the shape coefficient was calculated to identify polyester/cotton fiber category. The experimental results indicated that the data and results obtained by the newly-designed digital analysis method which is based on shape coefficient in this paper can be used to identify the polyester/cotton fiber category, showing a broad application prospect in textile quality control, including the developments of concerned equipments, methods and standards.

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  Cite this article

[IEEE Style]

I. o. I. D. M. f. I. o. P. F. Category, "Investigation on Image-Based Digital Method for Identification on Polyester/Cotton Fiber Category," Fibers and Polymers, vol. 22, no. 6, pp. 1774-1783, 2021. DOI: 10.1007/s12221-021-0802-7.

[ACM Style]

Investigation on Image-Based Digital Method for Identification on Polyester/Cotton Fiber Category. 2021. Investigation on Image-Based Digital Method for Identification on Polyester/Cotton Fiber Category. Fibers and Polymers, 22, 6, (2021), 1774-1783. DOI: 10.1007/s12221-021-0802-7.

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