Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

November 11, 2024


Pages


DOI

Article

A Study on the Reproduction of Traditional Chinese Painting Techniques and Their Innovation under Digital Transformation

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Authors

Lei Ma Affiliation:
School of Architecture and Art Design, Inner Mongolia University of Science & Technology, Baotou, Inner Mongolia, 014010, China.
, Xinyi Pan Affiliation:
College of Literature Art, Shihezi University, Shihezi, Xinjiang, 832061, China.
, Jingdong Liang Affiliation:
Faculty of Education, Northeast Normal University, Changchun, Jilin, 130000, China.
and Yun Xue Affiliation:
School of Architecture and Art Design, Inner Mongolia University of Science & Technology, Baotou, Inner Mongolia, 014010, China.


Abstract

After a long period of development and evolution, Chinese painting has formed a set of regular artistic language, which highlights the national characteristics of Chinese painting and is an important factor distinguishing it from other works of art. As the main characteristic of Chinese painting, this paper analyzes the traditional techniques of Chinese painting according to the three characteristics of Chinese painting: line, ink, and color, and analyzes the language of programed techniques. Then the method of digital reproduction of traditional techniques of Chinese painting is proposed and elaborated with the example of “The Western Garden of Elegant Gathering”. Subsequently, for the complexity of hand movement recognition of Chinese painting techniques, this paper proposes a sample splitting and re-fusion algorithm RCF based on sEMG to optimize the hand movement signals and construct a hand movement recognition model based on surface EMG signals. Through empirical analysis, the SVM classifier used in this paper has an average recognition correctness rate of 98%, which is 6% and 3% higher than BP and LDA, respectively. Meanwhile, the recognition accuracy of the hand movements of the eight techniques is all above 95%, with an average recognition accuracy of 98.5%. The mean value of all five indicators of the experience evaluation of Chinese painting techniques reproduction and innovation exceeded 4 points, and the overall average score was 4.542, indicating that the experiencers were very satisfied with the experience of Chinese painting techniques reproduction to innovation in this paper. The research of this paper provides theoretical and technical guidance for the reproduction and innovation of traditional Chinese painting techniques, as well as ideas for the organic combination of digital technology and traditional Chinese paintings.


Keywords

Programmed language, sEMG, RCF, Hand movement recognition, Chinese painting techniques, 68V35


Citation

Ma, L., Pan, X., Liang, J., & Xue, Y. (2024). A study on the reproduction of traditional chinese painting techniques and their innovation under digital transformation. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-3168

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