Skew Detection and Yarns Density Calculation for Woven Fabric
DOI:
10.3993/jfbi12201414
Journal of Fiber Bioengineering & Informatics, 7 (2014), pp. 615-625.
Published online: 2014-07
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@Article{JFBI-7-615,
author = {Junfeng Jing, Shan Liu, Lei Zhang and Pengfei Li},
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
AU - Junfeng Jing, Shan Liu, Lei Zhang & Pengfei Li
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 and Pengfei Li. (2014). 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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