Application of artificial intelligence in analysis and preservation of traditional Chinese painting techniques

Abstract

Renowned for its scientific, artistic, and cultural innovations, the Han dynasty marked a significant turning point in Chinese history. The use of ink, brushstrokes, and thematic components influenced by Confucianism, Daoism, and other philosophical traditions are few of the creative styles and methods that were popular during this period in Han painting (HP). HP is distinguished by its delicate brushstrokes, subtle ink washes, and meticulous attention to detail. It frequently depicts themes of nature, landscapes, animals, and everyday life. As an integral part of China’s creative legacy, this form of art continues to be honored and it had a significant effect on later Chinese painting (CP) shape. HPs’ color qualities and Patterns would suffer significant deterioration with time. Research on the culture indicates that Han art is limited. In addition, there is a powerful correlation between changes in the reliability of CP and the environment. The conservation and study of traditional Chinese HP techniques by artificial intelligence (AI) offers a possible path forward for the preservation and knowledge of this historic art form. In this research, the link between safeguarding the environment and the patterns (P), color (C), and shapes (S) of CP was investigated using a novel earthworm tuned recurrent neural network (EW- TRNN). We gathered Hans CP datasets as experimental data. Image preprocessing using Gaussian blur filter for noise reduction. Feature extraction employs the Gray Level Co-occurrence Matrix (GLCM) to capture the textural P and brushwork style characteristics. The study’s findings demonstrate that the suggested approach is more authentic in predicting the P, S, and C features of Chinese artworks. Finally, we conclude by stating that we may improve preservation efforts, research, and public happiness of HPs among contemporary audiences by utilizing AI-driven methodologies. This work assurance the endurance and accessibility of HPs for future generations by highlighting the revolutionary possibility of AI in bridging the gap between tradition and technological advances.