Research of Fabric Weave Pattern’s Recognition Using Texture Orientation Features
A novel approach is proposed for measuring fabric texture orientations and recognizing weave patterns. Wavelet transform is suited for fabric image decomposition and Radon Transform is fit for line detection in fabric texture. Since different weave patterns have their own regular orientations in original image and sub-band images decomposed by Wavelet transform, these orientations features are extracted and used as SOM and LVQ inputs to achieve automatic recognition of fabric weave. The experimental results show that the neural network of LVQ is more effective than SOM. The contribution of this study is that it not only can identify fundamental fabric weaves but also can classify double layer and some derivative twill weaves such as angular twill and pointed twill.
Liangchi Zhang, Chunliang Zhang and Zichen Chen
J. Q. Shen and X. Zou, "Research of Fabric Weave Pattern’s Recognition Using Texture Orientation Features", Advanced Materials Research, Vols. 328-330, pp. 1763-1767, 2011