Automatic Generation System of Computer Oil Painting Based on Red Spirit
- DOI
- 10.2991/978-94-6463-046-6_43How to use a DOI?
- Keywords
- Oil Painting; Image Processing Technology; Computer; Red Spirit
- Abstract
In the oil painting creation in the direction of red spirit, the oil painting is generally in a realistic style, and the emphasis is on highlighting the historical stories in the oil painting. In the optimized creation of the red spirit, computer technology can be used to quickly complete the creation from historical images to oil paintings. In this paper, according to the requirements of the red spirit for optimized creation, an optimized generation system based on computer image processing technology is constructed. After the system receives and processes the original image, it can obtain sampling points in the form of a grid, and determine the optimized stroke direction, brush pixel value and radius according to the pixel value of the source image, and finally realize the conversion from other images to oil paintings. This system can improve the efficiency of red spirit oil painting creation, and can make the processed images have the characteristics of optimized drawing, so as to meet people’s individual needs for oil painting creation.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Tianhui Shui AU - Yuetong Lei PY - 2022 DA - 2022/12/17 TI - Automatic Generation System of Computer Oil Painting Based on Red Spirit BT - Proceedings of the 2022 2nd International Conference on Computer Technology and Media Convergence Design (CTMCD 2022) PB - Atlantis Press SP - 365 EP - 372 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-046-6_43 DO - 10.2991/978-94-6463-046-6_43 ID - Shui2022 ER -