Weave pattern recognition by measuring fiber orientation with Fourier transform. Issue 4 (3rd April 2017)

• Record Type: Journal Article
• Authors: Zhang, Jie; Pan, Ruru; Gao, Weidong; Xiang, Jun
• Is Part Of: Journal of the Textile Institute. Volume 108:Issue 4(2017)
• Page Start: 622
• Page End: 630
• Publication Date: 2017-04-03
• Subjects: Yarn-dyed fabric -- weave pattern recognition -- yarn float -- fiber orientation measurement -- two-dimensional Fourier transform; Textile industry -- Periodicals; Textile fabrics -- Periodicals; Periodicals; 677.005
• DOI: 10.1080/00405000.2016.1177865
• Languages: English
• ISSNs: 0040-5000

Abstract

Abstract: An effective method based on measuring the fiber orientation of yarn floats with two-dimensional Fourier transform (2-D FFT) is proposed to recognize the weave pattern of yarn-dyed fabric in the high-resolution image. The recognition process consists of four main steps: 1. High-resolution image reduction, 2.Fabric image skew correction, 3.Yarn floats localization, 4. Yarn floats classification. Firstly, the high-resolution image is reduced by the nearest interpolation algorithm. Secondly, the skew of the fabric image is corrected based on Hough transform. Thirdly, the yarn floats in the fabric image is localized by the yarns segmentation method based on the mathematical statistics of sub-images. Fourthly, the high-resolution image is corrected and its yarns are segmented successively according to the inspection information of the reduced image. The fiber orientations are detected by 2-D FFT, and the yarn floats are classified by k-means clustering algorithm. Experimental results and discussions demonstrate that, by measuring the fiber orientation of yarn floats, the proposed method is effective to recognize the yarn floats and the weave pattern for yarn-dyed, solid color, and gray fabrics.