Printed Texture Guided Color Feature Fusion for Impressionism Style Rendering of Oil Paintings

Jing Geng (Lead / Corresponding author), Li’e Ma (Lead / Corresponding author), Xiaoquan Li, Xin Zhang, Yijun Yan (Lead / Corresponding author)

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Abstract

As a major branch of Non-Photorealistic Rendering (NPR), image stylization mainly uses computer algorithms to render a photo into an artistic painting. Recent work has shown that the ex-traction of style information such as stroke texture and color of the target style image is the key to image stylization. Given its stroke texture and color characteristics, a new stroke rendering method is proposed. By fully considering the tonal characteristics and the representative color of the original oil painting, it can fit the tone of the original oil painting image into a stylized image whilst keeping the artist’s creative effect. The experiments have validated the efficacy of the proposed model in comparison to three state-of-the-arts. This method would be more suitable for the works of pointillism painters with a relatively uniform style, especially for natural scenes, otherwise, the results can be less satisfactory.

Original languageEnglish
Article number3700
Number of pages16
JournalMathematics
Volume10
Issue number19
DOIs
Publication statusPublished - 9 Oct 2022

Keywords

  • feature fusion
  • image stylization
  • non-photorealistic rendering (NPR)

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • General Mathematics
  • Engineering (miscellaneous)

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