journal article·2021-10

Image-based Bilateral Beard Method for measuring weight-based short fiber contents in raw cotton and semi-finished slivers

Chenhong Lang, Mingming Zhang, Tingrong Wang, Jingye Jin, Fumei Wang, Bugao Xu, Yiping Qiu

Textile Research Journal· Volume 91· Issue 19-20
Publisher page

Abstract

In this paper, an economical way for accurately determining weight-based short fiber contents in raw cotton and semi-finished slivers by utilizing special bilateral beard specimens and image processing was introduced. In the specimen preparation, cotton fibers were drawn by a manual device into a sliver, then the sliver was combed to form a bilateral beard specimen, and finally the bilateral beard was scanned to generate a grayscale image from which a relative fiber number curve was extracted. An algorithm for calculating the weight-based short fiber contents based on the curve was proposed. Five types of cottons were repetitively measured to investigate the robustness of the results of [Formula: see text] and [Formula: see text], with the weight ratio of fibers shorter than 12.7 and 16 mm, respectively. The results showed that measuring two bilateral beards for each sample could keep the error rate lower than 15%, while four specimens kept the error rate lower than 10%. Compared with AFIS Pro 2, this Image-based Bilateral Beard Method provided results with lower standard deviations and variable coefficients, signifying its analogous or better robustness. In addition, 37 samples from some of the world’s major producing areas were measured by this method and AFIS Pro 2, and a Bland–Altman analysis confirmed a good agreement between the results from the two methods. As only a manual fiber drawing device and an office scanner are needed, this Image-based Bilateral Beard Method is clearly a cheap approach for accurately determining the short fiber contents in raw cotton and semi-finished slivers.
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Research context

OpenAlex topics: Textile materials and evaluations · Industrial Vision Systems and Defect Detection · Optical measurement and interference techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Textiles and Apparel, Quanzhou Normal University, China

Qiandongnan Vocational & Technical College for Nationalities, China

College of Textiles, Donghua University, China

Department of Merchandising and Digital Retailing, University of North Texas, USA

Funding

Fujian Provincial Natural Science Foundation of China · National Natural Science Foundation of China · Quanzhou City Science & Technology Program of China

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