AI-Driven Innovation in Intangible Cultural Heritage:A Semiotic Analysis of Door-God Woodblock Prints Using Diffusion Models

As a form of China’s intangible cultural heritage, woodblock New Year prints face challenges, including insufficient innovative expression and a weakening resonance with contemporary audiences. Using the “Qin Qiong and Jing De” Door-God prints as a case study, this research constructs a Peircean triadic semiotic model and, under controlled conditions, conducts two types of image-innovation studies: traditional manual design and diffusion-model-assisted design. Quantitative indicators are established using AHP and FCE to compare visual appeal, cultural identity, and emotional resonance. The results show that AI-assisted design has advantages in visual appeal and creative diversity, while traditional design performs better in cultural identity and semantic stability. Experiments with general audiences confirm that AI outputs are readable but still fall short of manual design in terms of stability with respect to cultural conventions. This study proposes a “diffusion models × semiotics × quantitative evaluation” framework that provides a heritage-science-oriented analytical framework for evaluating the semantic sustainability of AI-generated cultural heritage imagery.