Generating Color Scribble Images using Multi-layered Monochromatic Strokes Dithering

Yi-Hsiang Lo
National Tsing Hua University
Ruen-Rone Lee
Industrial Technology Research Institute
Hung-Kuo Chu
National Tsing Hua University
Computer Graphics Forum (Proc. of Eurographics 2019)


Color scribbling is a unique form of illustration where artists use compact, overlapping, and monochromatic scribbles at microscopic scale to create astonishing colorful images at macroscopic scale.  The creation process is skill-demanded and time-consuming, which typically involves drawing monochromatic scribbles layer-by-layer to depict true-color subjects using a limited color palette delicately.  In this work, we present a novel computational framework for automatic generation of color scribble images from arbitrary raster images.  The core contribution of our work lies in a novel color dithering model tailor-made for synthesizing a smooth color appearance using multiple layers of overlapped monochromatic strokes.  Specifically, our system reconstructs the appearance of the input image by (i) generating layers of monochromatic scribbles based on a limited color palette derived from input image, and (ii) optimizing the drawing sequence among layers to minimize the visual color dissimilarity between dithered image and original image as well as the color banding artifacts.  We demonstrate the effectiveness and robustness of our algorithm with various convincing results synthesized from a variety of input images with different stroke patterns.  The experimental study further shows that our approach faithfully captures the scribble style and the color presentation at respectively microscopic and macroscopic scales, which is otherwise difficult for state-of-the-art methods.


To be added


To be added



  title={Generating Color Scribble Images using Multi-layered Monochromatic Strokes Dithering},
  author={Lo, Yi-Hsiang and Lee, Ruen-Rone and Chu, Hung-Kuo},
  booktitle={Computer Graphics Forum (Proc. Eurographics)},

Full Paper

Full Paper (57MB)