Machine Learning-Based Intelligent Image Color Processing for Color Teaching Analysis of Chinese Painting

Abstract

Color itself is a beautiful and wonderful existence. Chinese traditional colors contain Chinese aesthetic taste and ancient cultural precipitation. It is said that color is a way to understand the world, while traditional Chinese color is integrated into life and caring for the soul [15]. With the continuous development of science and technology, computers are widely used in various fields, and intelligent image color processing technology is an independent theoretical and technical field, but it is also an extremely important technical support for machine perspective graphics processing. In this paper, combined with intelligent image color processing technology, the color teaching of Chinese painting is studied, and based on the wavelet variant, the best blur system parameters are used to obtain high-quality images using BFPSO, PSO, and BFO learning mechanisms to form suitable coding. Through the experiment, the color of Chinese painting is tested and verified by intelligent image color processing technology, and through the experimental results, it can be seen that the accuracy rate and recall rate after intelligent image processing technology are close to 1, indicating that, after optimizing with BFPSO algorithm, the optimal solution is given priority to a certain extent. Therefore, the use of intelligent image color processing technology has further improved the color teaching of Chinese painting.