<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

Teaching Chinese Painting Colour Based on Intelligent Image Processing Technology

Donghua University, Key Laboratory of Modern Fashion Design and Technology, Ministry of Education, Donghua University

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper constructs a Chinese painting color teaching platform based on intelligent image color processing technology. Firstly, the region segmentation...

Teaching Chinese Painting Colour Based on Intelligent Image Processing Technology

Online veröffentlicht: 11. Nov. 2023

Seitenbereich: -

Eingereicht: 18. Jan. 2023

Akzeptiert: 22. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.01088

Schlüsselwörter
Image color processing, Color teaching, Blur detection, Gradient optimization, Peak signal-to-noise ratio

© 2023 Guangyu Yang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Teaching Chinese Painting Colour Based on Intelligent Image Processing Technology

Online veröffentlicht: 11. Nov. 2023

Seitenbereich: -

Eingereicht: 18. Jan. 2023

Akzeptiert: 22. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.01088

SchlüsselwörterImage color processing, Color teaching, Blur detection, Gradient optimization, Peak signal-to-noise ratio

© 2023 Guangyu Yang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Image color processing, Color teaching, Blur detection, Gradient optimization, Peak signal-to-noise ratio