Automatic recognition of fabric nature by using the approach of texture analysis

被引:46
作者
Kuo, Chung-Feng Jeffrey [1 ]
Tsai, Cheng-Chih [1 ]
机构
[1] Natl Taiwan Univ Sci & Technol, Intelligence Control & Simulat Lab, Dept Polymer Engn, Taipei, Taiwan
关键词
fabric nature; co-occurrence matrix; wavelet transformation; computer vision;
D O I
10.1177/0040517506063917
中图分类号
TB3 [工程材料学]; TS1 [纺织工业、染整工业];
学科分类号
0805 ; 080502 ; 0821 ;
摘要
This paper proposes an approach to texture analysis that could be used to recognize the fabric nature and type of the main weaving texture. First, the color scanner captures the fabric image and saves it as a digital image and then the wavelet transformation is used to display the image texture. The co-occurrence matrix is then be applied to calculate the texture characteristics, such as angular second moment, entropy, homogeneity, and contrast, and finally, the learning vector quantization networks (LVQN) are adopted as a classifier to categorize the fabric nature and the type of weaving texture. The experimental result showed that this approach could automatically and accurately classify the fabric nature, including woven fabric, knitted fabric and non-woven fabric, and the type of its main weaving texture, such as plain, twill or satin weave, single or double knitted and non-woven fabric.
引用
收藏
页码:375 / 382
页数:8
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