Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Different inks may have different mechanical and/or optical properties. Existing Yule-Nielsen modified Neugebauer spectral prediction models assume however that the inks forming a color halftone behave similarly, i.e. that a single n-factor can model the lateral propagation of light within the paper as well as non-uniformities of the ink dot thickness profiles. However, if the inks have very different optical or mechanical properties, each ink may be separately modeled with its specific n-factor. In order to predict the reflection spectrum of such color halftones, we extend the ink spreading enhanced Yule-Nielsen modified spectral Neugebauer (EYNSN) model by calculating for each halftone an optimal n-factor as an average of the ink specific n-factors weighted by a parabolic function of the ink surface coverages. We compare the prediction accuracies of the standard EYNSN model where each halftone is predicted by making use of one global n-factor with the predictions accuracies of the extended EYNSN model where each halftone is predicted with its corresponding optimal n-factor derived from the individual ink-specific n-factors. For inks having very different optical and/or mechanical properties, we observe an improvement of the prediction accuracies.
Frank Nüesch, Jakob Heier, Sina Abdolhosseinzadeh, Mohammad Jafarpour