@Article{JFBI-12-193,
author = {Yu , ZhicaiZhong , Yueqi and Xie , Haoyang},
title = {Matching Fabric Based on Wavelet Kernel Signature (WKS) and Drape Indicators},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2019},
volume = {12},
number = {4},
pages = {193--203},
abstract = {<p>The drape performance of the fabric is an important part of the fabric style, as well as a special expression
of the structural parameters and mechanical properties. The comprehensive drape performance of fabric
can support fabric matching. This study was conducted to match fabric based on 3D triangular meshes
of draped fabrics. Firstly, the three-dimensional (3D) point cloud of draped fabric was scanned with a
self-built 3D scanning device followed with triangulation. Secondly, three drape indicators, i.e., drape
coefficient, the number of fabric drape nodes, and the solid rate of a draped fabric was extracted, as
well as the wavelet kernel signatures (WKS) of triangular meshes. The WKS of vertices on the 3D
boundary was selected and clustered into different classes with K-Means. With the cluster centers, the
WKS of vertices on the boundary was encoded into a vector with a fixed length. Finally, two methods
for matching fabrics were proposed based on WKS+DR and a vector consisting of three drape indicators
separately. The results show that WKS+DR outperforms the vector consisting of drape indicators in
characterizing the drape configuration details of a draped fabric. The accuracy of the method based on
WKS+DR could reach 89.6%. The fabrics obtained with this method are close to the matching fabrics
in both drape-ability and details of a triangle surface.</p>},
issn = {2617-8699},
doi = {https://doi.org/10.3993/jfbim00327},
url = {http://global-sci.org/intro/article_detail/jfbi/13572.html}
}