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基于太赫兹时域光谱的纺织品识别与分类

[Identification and classification of textiles based on terahertz time domain spectroscopy].

作者信息

Cao Bing-hua, Fan Meng-bao, Jing Sheng-yu

机构信息

School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou 221008, China.

出版信息

Guang Pu Xue Yu Guang Pu Fen Xi. 2010 Jul;30(7):1748-51.

Abstract

A method to discriminate textiles was proposed based on terahertz time-domain spectroscopy (THz-TDS) and clustering analysis, and some typical cotton textiles were investigated to prove its feasibility. Their time domain waveforms were measured using THz-TDS system and then their absorption spectra were obtained. Principal component analysis (PCA) was applied to extract features of the data, and then Mahalanobis distance discriminant method was employed to classify these materials. The results show that this method can classify these five textiles accurately. It indicates that the method to classify textiles is feasible which combines PCA and Mahalanobis distance discriminant method based on their THz absorption spectra. The proposed method has a potential for identifying textiles of similar composition.

摘要

提出了一种基于太赫兹时域光谱(THz-TDS)和聚类分析的纺织品鉴别方法,并对一些典型的棉纺织品进行了研究以证明其可行性。使用THz-TDS系统测量其时域波形,然后获得它们的吸收光谱。应用主成分分析(PCA)提取数据特征,然后采用马氏距离判别法对这些材料进行分类。结果表明,该方法能够准确地对这五种纺织品进行分类。这表明基于纺织品太赫兹吸收光谱结合PCA和马氏距离判别法的纺织品分类方法是可行的。所提出的方法在识别成分相似的纺织品方面具有潜力。

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