A generic pigment model for digital painting

Songhua Xu, Haisheng Tan, Xiantao Jiao, Francis C.M. Lau, Yunhe Pan

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

We propose a generic pigment model suitable for digital painting in a wide range of genres including traditional Chinese painting and water-based painting. The model embodies a simulation of the pigment-water solution and its interaction with the brush and the paper at the level of pigment particles; such a level of detail is needed for achieving highly intricate effects by the artist. The simulation covers pigment diffusion and sorption processes at the paper surface, and aspects of pigment particle deposition on the paper. We follow rules and formulations from quantitative studies of adsorption and diffusion processes in surface chemistry and the textile industry. The result is a pigment model that spans a continuum from the very wet to the very dry brush stroke effects. We also propose a new pigment mixing method based on machine learning techniques to emulate pigment mixing in real life as well as to support the creation of new artificial pigments. To experiment with the proposed model, we embedded the model in a sophisticated digital brush system. The combined system exhibits interactive speed on a modest PC platform. http://www.cs.hku.hk/ ∼songhua/pigment provides supplementary materials for this paper.

Original languageEnglish (US)
Pages (from-to)609-618
Number of pages10
JournalComputer Graphics Forum
Volume26
Issue number3
DOIs
StatePublished - Sep 2007

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design

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