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Textile Research Journal
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Automatic Recognition of Fabric Nature by Using the Approach of Texture Analysis

Chung-Feng Jeffrey Kuo

Intelligence Control and Simulation Laboratory, Department of Polymer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, Republic of China, jeff{at}tx.ntust.edu.tw

Cheng-Chih Tsai

Intelligence Control and Simulation Laboratory, Department of Polymer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, Republic of China

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.

Key Words: fabric nature • co-occurrence matrix • wavelet transformation • computer vision

Textile Research Journal, Vol. 76, No. 5, 375-382 (2006)
DOI: 10.1177/0040517506063917
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