Machine vision of textile testing and quality research

Issue title: Special Section: Fuzzy Logic for Analysis of Clinical Diagnosis and Decision-Making in Health Care

Article type: Research Article

Authors: Li, Xiaomian^{a; b} | Shu, Yufeng^{a; b; *} | Zuo, Dali^{a; b} | Zhang, Junhua^{a; b} | Chen, Zhanshuo^{a; b} | Gan, Haoxian^{a; b} | Li, Junlong^{a; b} | Li, Juntao^{a; b} | Chen, Kaiwen^{a; b} | Yang, Guohui^{a; b}

Affiliations: [a] Department of Mechanical and Electrical Engineering, DongGuan Polytechnic, DongGuan, China | [b] Guangdong Textile Industry Intelligent Detection Engineering Technology Research Center (DGPT), DongGuan, China

Correspondence: [*] Corresponding author. Shu Yufeng, E-mail: shuyf@dgpt.edu.cn.

Abstract:  In today’s globalized economy, various industries are promoting product transformation and upgrading. The textile industry is also facing a harsh international situation and fierce market competition. While constantly promoting the upgrade of automation equipment, the original quality control mode relying on manual testing has been unable to meet the modern production requirements and the market demand for product quality. This paper investigates the product inspection and quality control in the textile industry at home and abroad, and puts forward the application of machine vision technology in textile automated inspection and quality control, so As to strengthen the product quality control system and improve the product’s physical quality. By studying the composition of machine vision detection technology, this paper studies the two core technologies of image acquisition and image processing in machine vision, summarizes and analyzes the common defects of textile Products, and proves that the common defects can be detected and repaired in time by machine vision detection method.

Keywords: Machine vision, defect, automatic detection, image processing, textiles

DOI: 10.3233/JIFS-179407

Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 319-325, 2020