Unsupervised grouping of industrial textile dyes using K-means algorithm and optical fibre spectroscopy

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URI: http://hdl.handle.net/10902/2468
ISSN: 1996-756X
ISSN: 0277-786X
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Autoría
Cubillas de Cos, Ana María; Conde Portilla, Olga MaríaAutoridad Unican; Anuarbe Cortés, PedroAutoridad Unican; Quintela Incera, AntonioAutoridad Unican; López Higuera, José MiguelAutoridad Unican
Fecha
2010-09-08
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© 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Publicado en
Proceedings of SPIE, 2010, vol. 7653, 76533J
Fourth European Workshop on Optical Fibre Sensors, Oporto, 2010
Editorial
SPIE Society of Photo-Optical Instrumentation Engineers
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Palabras clave
Optical fiber sensors
Absorption spectroscopy
Textile dyes
K-means clustering
Principal component analysis (PCA)
Resumen/Abstract
A method for the unsupervised clustering of optically thick textile dyes based on their spectral properties is demonstrated in this paper. The system utilizes optical fibre sensor techniques in the Ultraviolet-Visible-Near Infrared (UV-Vis-NIR) to evaluate the absorption spectrum and thus the colour of textile dyes. A multivariate method is first applied to calculate the optimum dilution factor needed to reduce the high absorbance of the dye samples. Then, the grouping algorithm used combines Principal Component Analysis (PCA), for data compression, and K-means for unsupervised clustering of the different dyes. The feasibility of the proposed method for textile applications is also discussed in the paper.
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