This experimental study examines how generative AI reshapes the balance between perceptual fluency and cultural semiosis in children’s picture-book illustration by using a corpus derived from The Monkey King picture-book series, adapted from the classical Chinese novel Journey to the West. The study compares 224 handcrafted illustrations with 224 AI images generated by the Doubao platform (Seedream-3.0). Computational visual metrics, edge curvature and color entropy were calculated using OpenCV, while iconographic features were manually annotated with the UAM Image Tool (Mick O’Donnell, Universidad Autónoma de Madrid, Madrid, Spain). Quantitative analysis reveals statistically significant formal divergences between the two illustration modes. AI images generated by the Doubao platform exhibit a shift toward more outwardly convex contours and reduced color entropy, indicating smoother contours and chromatic homogenization that enhance perceptual accessibility. Iconographic analysis, however, demonstrates an attenuation of culturally specific symbols. High-frequency, contour-salient attributes are largely preserved, whereas low-frequency, ritualized, and hierarchically organized elements are frequently omitted or simplified. The findings reveal a tension between perceptual fluency and cultural–semantic stability in AI images generated by Doubao (ByteDance, Beijing, China), employing the Seedream 3.0 model. They support a framework of conditional applicability, with implications for picture-book illustration, cultural adaptation, and children’s visual-literacy education.
Du et al. (Thu,) studied this question.