Matthias Scheller Lichtenauer, Safer Mourad, Peter Zolliker, Klaus Simon. Classification of Paper Images to Predict Substrate Parameters Prior to Print. In Alain Trémeau, Raimondo Schettini, Shoji Tominaga, editors, Computational Color Imaging, Second International Workshop, CCIW 2009, Saint-Etienne, France, March 26-27, 2009. Revised Selected Papers. Volume 5646 of Lecture Notes in Computer Science, pages 150-159, Springer, 2009. [doi]
An accurate characterization of the substrate is a prerequisite of color management in print. The use of standard ICC profi les in prepress leaves it to the printer to match the fixed substrate characteristics contained in these pro files. 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 classi cation methods. For economical and ecological reasons it is preferable to test paper without printing it. We therefore propose non-destructive methods.