Color matching of ink-jet textile printing by inversion of forward Characterization models using genetic algorithm

Nowadays, the use of inversion of forward characterization models of the printer has been very much considered to color matching and color separation. The use of forward characterization models for textile printing is more complicated than the use of them for paper printing. The most important approaches that have been used for the characterization of the printer are Neugebauer, Yule-Nielsen modified Spectral Neugebauer (YNSN), and spectral n-value models. In this study, the prediction of CMYK digital values and inversion of forward characterization models were carried out by a Genetic Algorithm (GA). First, the forward characterization of the printer was performed and the optimum n-values in YNSN and spectral n-value models were obtained. The optimum n-values were used for the prediction of CMYK digital values, and the effective area coverages were obtained by GA. Then, the effective area coverages were converted to CMYK digital values. The obtained results show that the forward characterization of the printer by spectral n-value is better than others. Also, the best result of CMYK digital values prediction was obtained by GA using spectral n-value as the objective function. So, the quality of forward characterization model is one of the important factors in color matching by GA using inversion of the forward characterization models.