Painterly Rendering using Limited Paint Color Palettes

Abstract

We present a painterly rendering method for digital painting systems as well as visual feedback based painting machines that automatically extracts color palettes from images and computes mixture recipes for these from a set of real base paint colors based on the Kubelka-Munk theory. In addition, we present a new algorithm for distributing stroke candidates, which creates paintings with sharp details and contrasts. Our system is able to predict dry compositing of thinned or thick paint colors using an evaluation scheme based on example data collected from a calibration step and optical blending. We show results generated using a software stroke-based renderer and a painting machine.