Volume 9, Issue 1
Skew Correction and Density Detection of Knitted and Woven Fabric

Junfeng Jing, Panxia Hao, Pengfei Li, Lei Zhang & Hongwei Zhang

Journal of Fiber Bioengineering & Informatics, 9 (2016), pp. 53-61.

Published online: 2016-02

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  • Abstract

Automatic identification of fabric structure is a vital area of research. The skewing phenomenon is inevitable during the scanning process, so the fabric skew correction method based on projection profile analysis is proposed. First, Butterworth low-pass filter is applied to remove noises after skew correction of the fabric image. Then, power spectrum is obtained by Fast Fourier Transform (FFT), in which the peaks are extracted from the vertical and horizontal direction, respectively. Finally, the reconstructed image is obtained via Inverse Fast Fourier Transform (IFFT) according to the peaks, so that the information of warp and weft can be separated to calculate the warp and weft density. Experimental results show that the accuracy of the skew correction can be controlled within [-1°, 1°], and the detection accuracy of yarn density can reach 98%. The proposed method can accurately detect skew angle and density of woven and knitted fabrics.

  • Keywords

Skew Correction Projection Profile Analysis FFT Density Detection

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COPYRIGHT: © Global Science Press

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@Article{JFBI-9-53, author = {}, title = {Skew Correction and Density Detection of Knitted and Woven Fabric}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2016}, volume = {9}, number = {1}, pages = {53--61}, abstract = {Automatic identification of fabric structure is a vital area of research. The skewing phenomenon is inevitable during the scanning process, so the fabric skew correction method based on projection profile analysis is proposed. First, Butterworth low-pass filter is applied to remove noises after skew correction of the fabric image. Then, power spectrum is obtained by Fast Fourier Transform (FFT), in which the peaks are extracted from the vertical and horizontal direction, respectively. Finally, the reconstructed image is obtained via Inverse Fast Fourier Transform (IFFT) according to the peaks, so that the information of warp and weft can be separated to calculate the warp and weft density. Experimental results show that the accuracy of the skew correction can be controlled within [-1°, 1°], and the detection accuracy of yarn density can reach 98%. The proposed method can accurately detect skew angle and density of woven and knitted fabrics.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbim00179}, url = {http://global-sci.org/intro/article_detail/jfbi/10591.html} }
TY - JOUR T1 - Skew Correction and Density Detection of Knitted and Woven Fabric JO - Journal of Fiber Bioengineering and Informatics VL - 1 SP - 53 EP - 61 PY - 2016 DA - 2016/02 SN - 9 DO - http://doi.org/10.3993/jfbim00179 UR - https://global-sci.org/intro/article_detail/jfbi/10591.html KW - Skew Correction KW - Projection Profile Analysis KW - FFT KW - Density Detection AB - Automatic identification of fabric structure is a vital area of research. The skewing phenomenon is inevitable during the scanning process, so the fabric skew correction method based on projection profile analysis is proposed. First, Butterworth low-pass filter is applied to remove noises after skew correction of the fabric image. Then, power spectrum is obtained by Fast Fourier Transform (FFT), in which the peaks are extracted from the vertical and horizontal direction, respectively. Finally, the reconstructed image is obtained via Inverse Fast Fourier Transform (IFFT) according to the peaks, so that the information of warp and weft can be separated to calculate the warp and weft density. Experimental results show that the accuracy of the skew correction can be controlled within [-1°, 1°], and the detection accuracy of yarn density can reach 98%. The proposed method can accurately detect skew angle and density of woven and knitted fabrics.
Junfeng Jing, Panxia Hao, Pengfei Li, Lei Zhang & Hongwei Zhang. (2019). Skew Correction and Density Detection of Knitted and Woven Fabric. Journal of Fiber Bioengineering and Informatics. 9 (1). 53-61. doi:10.3993/jfbim00179
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