| Abstrakt: |
Fabric, a versatile material composed of interwoven fibers, serves diverse purposes spanning from clothing and furnishings to industrial applications. It exists in both natural forms like cotton and wool, and synthetic forms such as polyester and nylon, each impacting characteristics like texture, breathability, and strength. Fabric structure refers to the construction of textiles, particularly evident in woven fabrics where yarns interlace perpendicular to each other, forming geometric patterns like plain, herringbone, and diamond. The textile industry continuously innovates fabric production techniques, including automated processes and software-driven quality control. This paper explores the development of a novel software system for automatic fabric structure detection, leveraging advanced algorithms to analyze images and categorize fabric patterns. This innovation holds promise for streamlining quality control and aiding design processes in industries like textiles and fashion. The research demonstrates the efficacy and accuracy of the software, marking a significant advancement in automated fabric analysis. Furthermore, it highlights the potential applications in textile manufacturing and quality assurance, contributing to improved efficiency and laying the groundwork for enhanced quality control processes. Ultimately, this paper aims to innovate fabric formula detection, empowering industries and consumers, fostering efficiency, and advancing knowledge in the field. [ABSTRACT FROM AUTHOR] |
