Volume 7, Issue 4
Skew Detection and Yarns Density Calculation for Woven Fabric

Junfeng Jing, Shan Liu, Lei Zhang & Pengfei Li

Journal of Fiber Bioengineering & Informatics, 7 (2014), pp. 615-625.

Published online: 2014-07

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  • Abstract

Automatic identification of fabric structure is a vital research according to the fabric texture. Due to the skewed phenomenon which is inevitable during the scanning process, Hough transform is utilized for skew detection. Then wavelet filter is proposed to separate warps from wefts to enhance the information in vertical and horizontal direction, respectively. Finally, the gray projection curve including peaks and valleys is obtained in warp and weft directions. According to the peaks, the yarns can be located and segmented apparently and the fabric density could be obtained. Experimental results show that the precision of skew detection could be controlled within 2° while the accuracy of yarns density detection can reach up to 100%, which demonstrate that the proposed method is effective in skew detection and fabric density calculation.

  • Keywords

Skew Detection Fabric Density Detection Hough Transform Wavelet Transform Gray Projection

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COPYRIGHT: © Global Science Press

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@Article{JFBI-7-615, author = {}, title = {Skew Detection and Yarns Density Calculation for Woven Fabric}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2014}, volume = {7}, number = {4}, pages = {615--625}, abstract = {Automatic identification of fabric structure is a vital research according to the fabric texture. Due to the skewed phenomenon which is inevitable during the scanning process, Hough transform is utilized for skew detection. Then wavelet filter is proposed to separate warps from wefts to enhance the information in vertical and horizontal direction, respectively. Finally, the gray projection curve including peaks and valleys is obtained in warp and weft directions. According to the peaks, the yarns can be located and segmented apparently and the fabric density could be obtained. Experimental results show that the precision of skew detection could be controlled within 2° while the accuracy of yarns density detection can reach up to 100%, which demonstrate that the proposed method is effective in skew detection and fabric density calculation.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbi12201414}, url = {http://global-sci.org/intro/article_detail/jfbi/4815.html} }
TY - JOUR T1 - Skew Detection and Yarns Density Calculation for Woven Fabric JO - Journal of Fiber Bioengineering and Informatics VL - 4 SP - 615 EP - 625 PY - 2014 DA - 2014/07 SN - 7 DO - http://doi.org/10.3993/jfbi12201414 UR - https://global-sci.org/intro/article_detail/jfbi/4815.html KW - Skew Detection KW - Fabric Density Detection KW - Hough Transform KW - Wavelet Transform KW - Gray Projection AB - Automatic identification of fabric structure is a vital research according to the fabric texture. Due to the skewed phenomenon which is inevitable during the scanning process, Hough transform is utilized for skew detection. Then wavelet filter is proposed to separate warps from wefts to enhance the information in vertical and horizontal direction, respectively. Finally, the gray projection curve including peaks and valleys is obtained in warp and weft directions. According to the peaks, the yarns can be located and segmented apparently and the fabric density could be obtained. Experimental results show that the precision of skew detection could be controlled within 2° while the accuracy of yarns density detection can reach up to 100%, which demonstrate that the proposed method is effective in skew detection and fabric density calculation.
Junfeng Jing, Shan Liu, Lei Zhang & Pengfei Li. (2019). Skew Detection and Yarns Density Calculation for Woven Fabric. Journal of Fiber Bioengineering and Informatics. 7 (4). 615-625. doi:10.3993/jfbi12201414
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