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Automatic woven fabric classification based on support vector machine
Author(s): P.F. Li, J. Wang, H.H. Zhang, J.F. Jing
Source: International Conference on Automatic Control and Artificial Intelligence (ACAI 2012), 2012, p. 581 - 584
Type: ConferencePaper
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In the textile industry, the classfication of woven fabric is usually manual. To improve work efficiency, this paper purposes a novel approach to extract image features for woven fabric's recognition automatically. Firstly, the local binary pattern method and the gray level co-occurrence matrix are adopted to compute the fabric image features. Then, the principal component analysis is utilized to reduce the high dimensional feature data. Lastly, a support vector machine is used as a classifier to recognize the woven fabric type. The experiments show that these methods can automatically and accurately classify the plain weave fabrics, twill weave fabrics and satin weave fabrics.

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