A Comparative Study on the Calligraphy Works of Wang Yangming and Zeng Guofan

Abstract

Introduction: This study performs a comparative analysis of the calligraphy works of Wang Yangming and Zeng Guofan using information science methodologies. Leveraging data from esteemed archives and digital libraries, such as the National Library of China and the Digital Archive of Chinese Calligraphy, we assembled a dataset comprising 150 works by Wang Yangming and 120 by Zeng Guofan. Our approach integrates qualitative and quantitative techniques, including image segmentation, feature extraction via convolutional neural networks, and similarity assessment through cosine similarity. We employed K-means clustering and conducted statistical analyses, such as t-tests, to compare feature means between the two artists. Additionally, a support vector machine (SVM) was utilized for classification, achieving an accuracy of 0.82. Multidimensional scaling (MDS) was applied to visualize the feature space, yielding a stress value of 0.15. Our results uncover distinct stylistic variations in stroke thickness, curvature, and spatial distribution, offering a comprehensive insight into the unique artistic signatures of Wang Yangming and Zeng Guofan.