An accurate characterization of the substrate is a prerequisite of color management in print. The use of standard ICC profiles in prepress leaves it to the printer to match the fixed substrate characteristics contained in these profiles. This triggers the interest in methods to predict, if a given ink, press and paper combination complies with a given characterization. We present an approach to compare physical and optical characteristics of papers in order to achieve such a prediction of compliance by classification methods. For economical and ecological reasons it is preferable to test paper without printing it. We therefore propose non-destructive methods. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Scheller Lichtenauer, M., Mourad, S., Zolliker, P., & Simon, K. (2009). Classification of paper images to predict substrate parameters prior to print. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5646 LNCS, pp. 150–159). https://doi.org/10.1007/978-3-642-03265-3_16
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