ArticlePolymers2026
Advanced Digital Imaging Assessment Method for Testing Surface Fuzzing in Textile Materials.
Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Textile materials made from staple fibers typically have protruding fibers on their surface, commonly referred to as surface hairiness. During fraying, the surface of the textile material is susceptible to damage, which affects its appearance and leads to fuzzing by roughening or the emergence of new fibers. The propensity for fuzzing is assessed using the standard visual method (EN ISO 12945-4:2020), which is intuitive and cost-effective but better suited for evaluating more pronounced surface phenomena, such as pilling. This is mainly because fuzzing is usually accompanied by pilling, and their simultaneous occurrence makes separate analysis difficult. As a result, instrumental methods for assessing fuzzing that provide a more objective evaluation are rarely reported. In this research, an advanced digital imaging assessment method was introduced, using an innovative apparatus that, with simultaneous assessment of pilling, enabled separate digital imaging of the same textile fabric specimen's surface fuzzing through a refined viewing angle. Additionally, newly developed software enabled digital analysis and acquisition of quantitative numerical values related to surface fuzzing. The research was conducted on six single-component woven fabrics made from cotton, wool, viscose, polyamide 6.6, polyester, and acrylic. Fuzzing was induced using an ICI tester (EN ISO 12945-1:2020) and a Martindale tester (EN ISO 12945-2:2020) through predefined box revolutions and fuzzing rubs ranging from 125 to 30,000. Fuzzing was assessed using both the standard visual method and the advanced digital imaging assessment method, with grading according to established classes based on the percentage change in fuzzing layer height. The results highlight the applicability of the advanced digital assessment method, as it separately captures the occurrence of fuzzing and distinguishes it from pilling.
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