Affiliation:
1. Yancheng Institute of Technology , Yancheng , Jiangsu , , China .
Abstract
Abstract
To ensure the effective preservation and evolution of traditional painting art, it is imperative to integrate contemporary art design concepts and methodologies. This paper focuses on the reconstruction of traditional Chinese painting elements, distilling and adapting its pattern, ink, and calligraphy components into a modern design framework. Specifically, the features of the pattern elements are identified and transformed using a feature point extraction algorithm combined with K-Means clustering. For ink and calligraphy elements, a fusion of self-attention mechanisms and Generative Adversarial Networks (GANs) facilitates the stylistic migration and conversion of these elements through the construction of distinct discriminators. Subsequent evaluation of the transformed painting elements utilized Importance-Performance Analysis (IPA) within a contemporary design context, aiming to assess the practical value of traditional painting elements in modern design. The findings indicate that the clarity of information (C1) and its accuracy and efficacy (C3) in the context of contemporary design achieved importance scores exceeding 3.6. Furthermore, the satisfaction scores for modeling (C10), color (C11), and imagery (C12) each surpassed 3.5, denoting a high level of satisfaction in the IPA of their conversion. The study enriches traditional artistic methods and conceptualizations, thereby enhancing their cultural depth and significance.
Reference17 articles.
1. Gao, H. (2019). The value and a preliminary study of the integration of traditional chinese painting and calligraphy & modern and contemporary art in primary school art teaching. International Education Studies, 12(6), 75.
2. He, Y. (2020). Analysis of the application of the modern graphic design and the traditional art design elements under the background of the multivariant integration. Basic & clinical pharmacology & toxicology.(S1), 127.
3. Chen, S. (2020). Exploration of artistic creation of chinese ink style painting based on deep learning framework and convolutional neural network model. Soft Computing, 24(9).
4. Fu, F., Lv, J., Tang, C., & Li, M. (2020). Multi-style chinese art painting generation of flowers. IET Image Processing.
5. Liang, Y. (2022). Analysis of the integration of chinese painting techniques in watercolor painting. Arts Studies and Criticism, 3(1), 37-40.