DescriptionColor printing plays an important role in the modern society. It is known that the color of printed images degrades gradually due to the fading and diffusion of the inks. Color degradation leads to a distortion or loss of the original information in printed images. Therefore, it is desirable to understand how the color of printed images changes over time. In this dissertation, we present degradation models to predict the characteristics of the ink fading and diffusion of printed images.
We begin by modeling the ink degradation from a physics-based perspective. Color images are printed by projecting small ink dots on medium, usually paper. This technique is called halftone printing. Halftone printing of color images results in a variety of ink mixtures and subsequently their potential catalytic fading. For the most commonly used Cyan-Magenta-Yellow-Black (CMYK) ink set, sixteen possible ink mixtures are generated during printing. A state transition diagram is then proposed for the ink fading in this multi-ink printing scenario. The ink area coverage is used as the performance indicator. Assuming constant fading and diffusion rates, we develop an ink fading model based on the differential equations according to the state transition diagram and an autoregressive ink diffusion model by discretizing the two-dimensional diffusion equation. The two models are then integrated into a single degradation model.
Further examination of the developed degradation models reveals that the fading or diffusion rate is equivalent to the hazard rate in reliability engineering. It is known that the hazard rate of the exponential failure time distribution is constant. Hence, the developed degradation model with constant fading and diffusion rates is equivalent to the multistate Markov process model with exponential transition time distribution. By using non-exponential transition time distributions, the fading and diffusion rates become time-varying and a more general semi-Markov process degradation model is developed accordingly.
Moreover, stochastic process models are investigated to provide stochastic area coverage prediction for the ink degradation. We first model the ink fading using the Hull-White/Vasicek (HWV) stochastic process. The HWV ink fading model considers that the variance of the ink area coverage shrinks as it approaches zero. Besides, spatial convolution is used to model ink diffusion. The two models are integrated into a spatio-temporal stochastic degradation model for the ink fading and diffusion of printed images. The cases of recurrent and non-recurrent time-varying fading and diffusion rates are investigated.
Inks on the paper degrade, so does the paper. The degradation of paper condition may in turn affect the degradation of the inks. Therefore, the investigation of the degradation modeling of ink fading and ink diffusion with ink-paper interactions is needed. Two aspects of the ink-paper interactions are considered, i.e., the effect of paper aging such as depolymerization and yellowing, and the fiber orientation of the paper.
The degradation process of printed images usually takes a very long time. An accelerated degradation model and the optimal design of accelerated degradation test planning is developed for accurate degradation prediction of printed images. The effects of three constant environmental stresses: temperature, humidity, and illumination (intensity), are investigated, and experimental data are used to validate the proposed model. The results show strong agreements between the proposed ink fading and ink diffusion prediction model and the actual experimental data.