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Proceedings Paper

NIR spectrophotometric system based on a conventional CCD camera
Author(s): Meritxell Vilaseca; Jaume Pujol; Montserrat Arjona
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Paper Abstract

The near infrared spectral region (NIR) is useful in many applications. These include agriculture, the food and chemical industry, and textile and medical applications. In this region, spectral reflectance measurements are currently made with conventional spectrophotometers. These instruments are expensive since they use a diffraction grating to obtain monochromatic light. In this work, we present a multispectral imaging based technique for obtaining the reflectance spectra of samples in the NIR region (800 - 1000 nm), using a small number of measurements taken through different channels of a conventional CCD camera. We used methods based on the Wiener estimation, non-linear methods and principal component analysis (PCA) to reconstruct the spectral reflectance. We also analyzed, by numerical simulation, the number and shape of the filters that need to be used in order to obtain good spectral reconstructions. We obtained the reflectance spectra of a set of 30 spectral curves using a minimum of 2 and a maximum of 6 filters under the influence of two different halogen lamps with color temperatures Tc1 = 2852K and Tc2 = 3371K. The results obtained show that using between three and five filters with a large spectral bandwidth (FWHM = 60 nm), the reconstructed spectral reflectance of the samples was very similar to that of the original spectrum. The small amount of errors in the spectral reconstruction shows the potential of this method for reconstructing spectral reflectances in the NIR range.

Paper Details

Date Published: 22 May 2003
PDF: 12 pages
Proc. SPIE 5011, Machine Vision Applications in Industrial Inspection XI, (22 May 2003); doi: 10.1117/12.474007
Show Author Affiliations
Meritxell Vilaseca, Univ. Politecnica de Catalunya (Spain)
Jaume Pujol, Univ. Politecnica de Catalunya (Spain)
Montserrat Arjona, Univ. Politecnica de Catalunya (Spain)

Published in SPIE Proceedings Vol. 5011:
Machine Vision Applications in Industrial Inspection XI
Martin A. Hunt; Jeffery R. Price, Editor(s)

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