Research of Fabric Weave Patterns Recognition Using Texture Orientation Features

摘要：

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.

关键词： Wavelet Transform Fabric Weave Texture Orientation Neural Network

作者: Jianqiang SHEN Xuan ZOU

作者单位: Shanghai-Hamburg Joint College, University of Shanghai for Science and Technology, Shanghai,200093, China

会议类型: 国际会议

会议名称: 2011 International Conference on Mechatronics and Materials Processing(2011年机电一体化与材料加工国际会议 ICMMP)

会议地点: 广州

会议语种:英文

页码: 1763-1767

在线出版日期: 2011-11-18（万方平台首次上网日期，不代表论文的发表时间）