Generating pointillism paintings based on Seurat's color composition

Yi Chian Wu, Yu Ting Tsai, Wen-Chieh Lin, Wen Hsin Li

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

This paper presents a novel example-based stippling technique that employs a simple and intuitive concept to convert a color image into a pointillism painting. Our method relies on analyzing and imitating the color distributions of Seurat's paintings to obtain a statistical color model. Then, this model can be easily combined with the modified multi-class blue noise sampling to stylize an input image with characteristics of color composition in Seurat's paintings. The blue noise property of the output image also ensures that the color points are randomly located but remain spatially uniform. In our experiments, the multivariate goodness-of-fit tests were adopted to quantitatively analyze the results of the proposed and previous methods, further confirming that the color composition of our results are more similar to Seurat's painting style than that of previous approaches. Additionally, we also conducted a user study participated by artists to qualitatively evaluate the synthesized images of the proposed method.

Original languageEnglish
Pages (from-to)153-162
Number of pages10
JournalComputer Graphics Forum
Volume32
Issue number4
DOIs
StatePublished - 1 Jan 2013

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