Maintaining accuracy of cellular Yule-Nielsen spectral Neugebauer models for different ink cartridges using principal component analysis

The replacement of used-up ink cartridges is unavoidable, but it makes the existing characterization model far from accurate, while recharacterization is labor intensive. In this study, we propose a new correction method for cellular Yule-Nielsen spectral Neugebauer (CYNSN) models based on principal component analysis (PCA). First, a small set of correction samples are predicted, printed using new ink cartridges, and then measured. Second, the link between the predicted and measured reflectance weights, generated by PCA, is determined. The experimental results show that the proposed method provides a significant and robust improvement, since not only the color change between original and new inks but also the systemic error of CYNSN modelsis taken into account in the method.