Paper Title:
Research of Fabric Weave Pattern’s Recognition Using Texture Orientation Features
  Abstract

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.

  Info
Periodical
Advanced Materials Research (Volumes 328-330)
Chapter
Chapter 3: Mechatronics and Automation
Edited by
Liangchi Zhang, Chunliang Zhang and Zichen Chen
Pages
1763-1767
DOI
10.4028/www.scientific.net/AMR.328-330.1763
Citation
J. Q. Shen, X. Zou, "Research of Fabric Weave Pattern’s Recognition Using Texture Orientation Features", Advanced Materials Research, Vols. 328-330, pp. 1763-1767, 2011
Online since
September 2011
Export
Price
$32.00
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