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Image Preprocessing for Artistic Robotic Painting

Артур Каримов, Ekaterina Kopets, Georgii Kolev, Sergey V. Leonov, Lorenzo Scalera, Денис Бутусов

Year
2021
Citations
15
Access
Open access

Abstract

Artistic robotic painting implies creating a picture on canvas according to a brushstroke map preliminarily computed from a source image. To make the painting look closer to the human artwork, the source image should be preprocessed to render the effects usually created by artists. In this paper, we consider three preprocessing effects: aerial perspective, gamut compression and brushstroke coherence. We propose an algorithm for aerial perspective amplification based on principles of light scattering using a depth map, an algorithm for gamut compression using nonlinear hue transformation and an algorithm for image gradient filtering for obtaining a well-coherent brushstroke map with a reduced number of brushstrokes, required for practical robotic painting. The described algorithms allow interactive image correction and make the final rendering look closer to a manually painted artwork. To illustrate our proposals, we render several test images on a computer and paint a monochromatic image on canvas with a painting robot.

Keywords

GamutComputer visionArtificial intelligenceComputer graphics (images)Computer scienceRendering (computer graphics)PaintingPreprocessorPerspective (graphical)Art

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