Reconstructing the Visual Language of Vietnamese Folk Paintings in Visual Communication Design: An AI Approach

Main Article Content

Nguyen Hong Ngoc
Luu Viet Thang

Abstract

Amid globalization and rapid digital transformation, vernacular visual languages risk marginalization or homogenization when translated into contemporary communication design. A pressing challenge lies in how these cultural codes can be reconstructed and expanded in ways that safeguard identity while responding to current aesthetic and technological demands. This study addresses this question by examining Vietnamese folk paintings - specifically the Đông Hồ and Hàng Trống traditions - positioned as emblematic cases of vernacular visual heritage. Despite their cultural significance, these traditions remain underexplored in systematic applications in modern media and design practices. The research employs a two-stage methodology. First, a case analysis of communication design works referencing Đông Hồ and Hàng Trống paintings is undertaken to extract essential components of their visual language, including motifs, color systems, symbolic structures, and compositional patterns. Second, an experimental AI-assisted pipeline is developed to generate extended variations of these elements through image synthesis and motif adaptation. The resulting outputs are assessed through expert evaluation and user testing to measure cultural resonance, design relevance, and adaptability across multimedia contexts. The findings reveal that artificial intelligence does not supplant vernacular traditions but instead acts as a generative medium for re-creating and diversifying heritage-based visual features. The study contributes to design scholarship in three ways: (i) demonstrating the viability of reconstructing vernacular visual languages within contemporary graphic communication; (ii) showing how AI can function simultaneously as a tool for preservation and innovation; and (iii) proposing a conceptual framework that links cultural values, design practice, and technological mediation. These insights advance interdisciplinary discourse on the futures of vernacular heritage in design research and practice.

Article Details

How to Cite
Ngoc, N. H., & Thang, L. V. (2025). Reconstructing the Visual Language of Vietnamese Folk Paintings in Visual Communication Design: An AI Approach. Journal of Cultural Analysis and Social Change, 10(3), 2486–2497. https://doi.org/10.64753/jcasc.v10i3.2779
Section
Articles