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Proceedings Paper

Fast qualitative analysis of textile fiber in near infrared spectroscopy based on support vector machine
Author(s): Donghui Wang; Shangzhong Jin; Bin Gan; Hongnian Feng
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Paper Abstract

The fast qualitative analysis of textile fiber is a crucial step in textile manufacture, export and inspection. This paper presents a near infrared spectroscopy classification method based on SVM for fast qualitative analysis of textile fiber. SVM is a new automatic classification tool and it has successfully been applied to standard classification tasks, such as text classification, pattern identification, bioinformatics and medical diagnosis. In this paper, SVM is extended into near infrared fast qualitative analysis of textile fiber for the first time. In this paper, eight kinds classification algorithms which are composed of two classifiers(C-SVC and ν-SVC) and four kernel functions (linear, polynomial, RBF and sigmoid) are used to do classification experiments and comparison analysis for ten kinds familiar textiles fiber. Experiment results show that it is feasible to apply SVM in fast qualitative analysis of textile fiber, and the optimal classifier algorithm and the corresponding experimental results are reported.

Paper Details

Date Published: 9 June 2006
PDF: 6 pages
Proc. SPIE 6149, 2nd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, 61493C (9 June 2006); doi: 10.1117/12.674348
Show Author Affiliations
Donghui Wang, Zhejiang Univ. (China)
Shangzhong Jin, China JiLang Univ. (China)
Bin Gan, China JiLang Univ. (China)
Hongnian Feng, Univ. of Shanghai for Science and Technology (China)


Published in SPIE Proceedings Vol. 6149:
2nd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies
Li Yang; Shangming Wen; Yaolong Chen; Ernst-Bernhard Kley, Editor(s)

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