@Article{JFBI-9-53,
author = {Junfeng Jing, Panxia Hao, Pengfei Li, Lei Zhang and Hongwei Zhang},
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}
}