Teaching Chinese Painting Colour Based on Intelligent Image Processing Technology

Author:

Yang Guangyu1,Zhou Honglei2

Affiliation:

1. 1 College of Fashion and Art Design , Donghua University , Shanghai , , China .

2. 2 College of Fashion and Art Design , Donghua University, Key Laboratory of Modern Fashion Design and Technology, Ministry of Education, Donghua University , Shanghai , , China .

Abstract

Abstract This paper constructs a Chinese painting color teaching platform based on intelligent image color processing technology. Firstly, the region segmentation method is used to reasonably segment the pixel points according to the similar values of color and texture parameters of the image. Then, the image’s primary color grayscale parameters are fuzzy, detected, equalized, and fused by color difference values. Finally, the gradient optimization algorithm is combined to identify and control the image color parameters. The results show that the highest value of peak signal-to-noise ratio can reach 73.4db for the images processed by the method of this paper, and the mean value of STRESS is kept between 0-10%. The intelligent image color processing technique has been proven to enhance the aesthetics and innovation of Chinese painting colors in students.

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Engineering (miscellaneous),Modeling and Simulation,General Computer Science

Reference21 articles.

1. Li, D., & Zhang, Y. (2020). Multi-instance learning algorithm based on lstm for chinese painting image classification. IEEE Access, 8, 179336-179345.

2. Xue, J., Guo, J., & Liu, Y. (2020). User-guided chinese painting completion–a generative adversarial network approach. IEEE Access, 8, 187431-187440.

3. Zhu, C., & Sun, K. (2018). Cryptanalyzing and improving a novel color image encryption algorithm using rt-enhanced chaotic tent maps. IEEE Access,18759-18770.

4. Yakun, C. (2017). Research on the application of chinese traditional art in the process of modern products design based on computer simulation. Boletin Tecnico/technical Bulletin, 55(6), 565-571.

5. Liang, S., Feng, S., Ganping, Z., & Huhai, L. (2019). On the role of painting in the development of ink and wash animation. Paper Asia, 2(1), 42-47.

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