Artificial intelligence-based fuzzy control algorithm for the fusion of chinese art painting colors with film

By merging the visual colors of traditional Chinese art painting with modern cinema, this research is demonstrating a method for expanding the color aesthetic of films. This research is specifically focusing on the use of an Artificial Intelligence based fuzzy control algorithm to successfully merge the colors of Chinese paintings with films. Existing methods for color merging either fail to address the subjective nature of color interpretation or do not have the flexibility to managing the uncertainty of color blending resulting in colors that are fuzzy, unnatural and or cannot be understood in the common goal of color merging. This study proposes an AI-Driven Fuzzy Logic Color Fusion (AI-FLCF) Framework that works by utilizing a deep learning based color feature extraction select dominant colors, textures, and tonal characteristics from both Chinese paintings and frames from films. The components responsible for color merging will take the extracted colors and use fuzzy rules defined using a fuzzy controller to provide a successful color merge. The AI-FLCF framework empowers filmmakers and digital artists to incorporate culturally rich color aesthetics into their films, resulting in enhanced visual coherence and artistic depth. Experimental results show that the framework achieves an HDT of 6.7–7.6, TSC of up to 0.93, TCR between 1.58 and 1.63, DCR of 0.82–0.85, CHI of 0.88–0.92, and RAT of 0.66–0.70, confirming its effectiveness in achieving visually seamless and culturally faithful film color fusion.