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Proceedings Paper

Spectral representation of paper opacity
Author(s): Jouni Haanpalo; Pertti Silfsten; Jussi P. S. Parkkinen; Timo Jaeaeskelaeinen
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Paper Abstract

Paper opacity is an important problem in the paper industry. In this paper we have studied methods to derive reflectance spectrum of an opaque pile of colored paper from the reflectance spectrum of the single sheet of the same paper type. Five opacity correction methods were tested. Four of them used algebraic equations for constructing corrected spectra and the fifth method was based on the multi-layer- perceptron (MLP) neural network. Two sample sets were used for testing opacity correction methods. The first set consisted of 9 colored newsprint samples and the second set was formed from 15 samples of colored photocopier paper. The measurements of both sample sets were done with Minolta CM-2002 spectrophotometer. The measured wavelength range was from 400 nm to 700 nm with 10 nm sampling interval. For both sample sets similar tests were made. The CIE L*a*b* color coordinates were calculated both for the spectra measured from opaque piles and for the opacity corrected spectra. For each sample the absolute color coordinate differences between the coordinates of the pile spectra and the corresponding corrected spectra were computed and the results of different methods were compared to each other. The method based on the transmittance of paper gave the best results with both test sets. The predefined error tolerance of 0.5 in the a* color coordinate was achieved. The MLP-network worked also fine but the results may have been affected by the small number of training samples. We have shown that paper opacity depends on wavelength and we have developed a method for deriving the color of an opaque pile of paper from the single sheet of paper of the same type.

Paper Details

Date Published: 26 September 1997
PDF: 9 pages
Proc. SPIE 3208, Intelligent Robots and Computer Vision XVI: Algorithms, Techniques, Active Vision, and Materials Handling, (26 September 1997); doi: 10.1117/12.290305
Show Author Affiliations
Jouni Haanpalo, Lappeenranta Univ. of Technology (Finland)
Pertti Silfsten, Lappeenranta Univ. of Technology (Finland)
Jussi P. S. Parkkinen, Lappeenranta Univ. of Technology (Finland)
Timo Jaeaeskelaeinen, Univ. of Joensuu (Finland)


Published in SPIE Proceedings Vol. 3208:
Intelligent Robots and Computer Vision XVI: Algorithms, Techniques, Active Vision, and Materials Handling
David P. Casasent, Editor(s)

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