Paper
22 December 1998 Prediction of colorimetric measurements in newspaper printing using neural networks
Hansjoerg Kuenzli, Anja Noser, Marcel Loher, Safer Mourad
Author Affiliations +
Abstract
For an optimum quality control in newspaper printing, patches printed with different combinations of CMYK should be calorimetrically measured. However, control strips with a large number of color patches cannot be included into the layout of newspapers, due to the additional space they need. Moreover, such control strips require a considerable amount of time for the measurement. To overcome these problems it is preferable to print and to analyze only a few color patches and to obtain most information out of these. A method using neural networks has been developed to predict color values of two and three-color overprints from those of the primary inks, as well as color values of the primary inks from the two and three-color overprints. The feature of the method is that spectra are predicted from which colorimetric values and densitometric values are derived. The accuracy of the predicted CIELab values of the primaries from those of the overprints is typically within (Delta) E*ab equals 1 for the two-color overprints, and within (Delta) E*ab equals 2 for the three-color overprints.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hansjoerg Kuenzli, Anja Noser, Marcel Loher, and Safer Mourad "Prediction of colorimetric measurements in newspaper printing using neural networks", Proc. SPIE 3648, Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts IV, (22 December 1998); https://doi.org/10.1117/12.334575
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KEYWORDS
Neural networks

Printing

Solids

Principal component analysis

Neurons

Statistical modeling

Curium

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