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FLEXO Magazine : May 2009
Existing ICC profi le color management for CMYK enables more advanced spot color management. SUBSTRATE PROFILES It is assumed that substrates can be characterized for properties that aff ect color reproduction. These properties can be quantifi ed using standardized measurement protocol. It is hypothesized that these properties can be assembled into a standardized fi le format that can be called upon in workfl ows and color management systems for predicting how a known spot color defi nition will reproduce. The known spot color defi nition needs to include the defi ned substrate profi le used when creating the color standard. What are substrate characteristics that can aff ect color reproduction? Some obvious choices include: • CIE LABCH color • Light scattering and absorption curves • Liquid absorption • Roughness • Gloss The challenge comes when developing mathematical prediction models of how these attributes work together to aff ect fi nal color appearance of, not only the solid color, but the entire tonal range and multiple spot color overprints. Some preliminary tests were completed in the Fall of 2008 with a Clemson student research group to perform a short experiment taking four ink colors (red, orange, purple, and green) across four substrates: coated SBS (solid bleached sulfate), uncoated SBS, opaque white poly, and cast gloss pressure sensitive. Substrates were quantifi ed using the metrics listed above. Color change (∆L, ∆c, ∆h) of each ink across specifi ed substrates was quantifi ed. The correlation of each substrate characteristic with ∆L, ∆c, and ∆h in each color ink was evaluated for coeffi cient of determination, or R2, through simple linear regression. If the substrate characteristic could be used to predict the lightness, chroma, or hue of the ink, a favorable R2 value would appear, and those characteristics were selected for the model. Some preliminary calculations were made based on interest- ing fi ndings in this investigative research project. The model was put to work using existing packaging samples, and it was found to predict certain elements of color change very well. This example is outlined in Table 1. This early result is used to generate interest for a larger research eff ort that is currently underway.