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Proceedings Paper

Adaptive modeling color measurement errors
Author(s): Guoping Qiu; Hsiao-Pei Lee; Ming Ronnier Luo
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Paper Abstract

A hybrid adaptive system incorporating linear regression and neural network has been developed for the correction of color measuring errors. The linear regression model is used to correct systematic errors while the neural network is used to correct the residue errors that the linear regression method is unable to remove. We use standard color materials from the National Physical Laboratory (NPL) as training samples and test the method using a variety of colors outside the training set. Experimental results are presented which show promising future of neural networks in color measuring industries.

Paper Details

Date Published: 16 September 1999
PDF: 10 pages
Proc. SPIE 3826, Polarization and Color Techniques in Industrial Inspection, (16 September 1999); doi: 10.1117/12.364323
Show Author Affiliations
Guoping Qiu, Univ. of Derby (United Kingdom)
Hsiao-Pei Lee, Univ. of Derby (United Kingdom)
Ming Ronnier Luo, Univ. of Derby (United Kingdom)


Published in SPIE Proceedings Vol. 3826:
Polarization and Color Techniques in Industrial Inspection
Elzbieta A. Marszalec; Emanuele Trucco, Editor(s)

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