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Calibrating the Yule-Nielsen modified spectral Neugebauer model with ink spreading curves derived from digitized RGB calibration patch images

N. P. Garg, A. K. Singla, R. D. Hersch

Journal of Imaging Science and Technology (JIST) Vol. 52, No. 4, paper 040908, 5 pages

The Yule-Nielsen modified spectral Neugebauer model (YNSN) enhanced for accounting for ink spreading in the different ink superposition conditions requires a photospectrometer to measure the reflectances of halftone calibration patches in order to compute the ink spreading curves mapping nominal ink surface coverage to effective ink surface coverage. Spectral measurements of dozens of halftone patch reflectance spectra is cumbersome and time consuming. As an alternative, we try to deduce the ink spreading curves from digitized RGB images of halftone calibration patches. By applying the Yule Nielsen broadband formula to the average RGB intensities, we deduce the effective dot surface coverages of halftone calibration patches at several nominal surface coverages. We then establish the ink spreading curves mapping nominal dot surface coverages to effective dot surface coverages. By weighting the contributions of the different ink spreading curves according to the ratios of colorant surface coverages, we predict according to the Yule-Nielsen modified spectral Neugebauer model (YNSN) the reflectance spectra of the test patches. We compare the prediction accuracy of the YNSN model calibrated by digitized RGB intensities of the calibration patches with the prediction accuracy of the same model calibrated by the spectral reflectances of these calibration patches. For 729 uniformly distributed test patches of cyan, magenta and yellow, printed with an ink jet printer at 600dpi and 75lpi, the mean ?E94 difference between predictions and measurements is 1.00 for spectral calibration and 1.33 for calibration with digitized RGB intensities.

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Last modified: 2009/01/27 10:56:10