Yarn apparent evenness detection based on L0 norm smoothing and the expectation maximization method. Issue 1 (January 2023)

• Record Type: Journal Article
• Authors: Zhang, Huanhuan; Zhu, Houchun; Yan, Kai; Jing, Junfeng; Su, Zebin
• Is Part Of: Textile research journal. Volume 93:Issue 1/2(2023)
• Page Start: 422
• Page End: 433
• Publication Date: 2023-01
• Subjects: Yarn apparent evenness -- L0 smoothing method -- expectation maximization segmentation algorithm -- morphological opening operation; Textile industry -- Periodicals; Textile fabrics -- Periodicals; Textile research -- Periodicals; Textiles et tissus -- Industrie et commerce -- Périodiques; Textiles et tissus -- Périodiques; Textiles et tissus -- Recherche -- Périodiques; Electronic journals; 677.005
• DOI: 10.1177/00405175221119838
• Languages: English
• ISSNs: 0040-5175

Abstract

During spinning, knitting and weaving processes, the yarn apparent evenness is an important factor, which determines the quality of subsequent spinning production and fabric performance. This paper presents a powerful method which is based on L0 norm smoothing and the expectation maximization method to detect the yarn apparent evenness. The L0 norm smoothing method is first applied to remove the noise and enhance the yarn apparent evenness diameter features. Then, the expectation maximization method and the morphological opening operation were used to obtain the yarn evenness. Finally, we calculated the yarn apparent evenness diameter and the coefficient of variation of the evenness of the yarn apparent diameter. Compared with the capacitive evenness testers, the Otsu detection method and the fuzzy C-means detection method, our method can accurately detect the yarn apparent evenness better than the selected state-of-the-art methods.