Innovative Color Management Methods for RGB Printing

Re-calibrating a printer in response to systematic changes is measurement and labor intensive. In this study, a fast correction method with cycle-to-cycle control was proposed. The process includes two steps: the creation of look-up table using a characterization data set, and image color compensation in conjunction with Windows printing architecture. Several types of correction models for determining printer characterization were proposed and evaluated, including polynomial models and neural network models. The most successful of these methods was the quadratic spline interpolation model, which removed most errors introduced by the changes of colorant and printing substrate. A significant reduction in error was realized by incorporating this technique into the color management program. Thesis Supervisor: Kamal Youcef-Toumi Title: Professor of Mechanical Engineering