A Novel CNN Model for Classification of Chinese Historical Calligraphy Styles in Regular Script Font

Author:

Huang Qing1,Li Michael2ORCID,Agustin Dan3ORCID,Li Lily2ORCID,Jha Meena2ORCID

Affiliation:

1. School of Education and the Arts, Central Queensland University, Rockhampton, QLD 4701, Australia

2. School of Engineering and Technology, Central Queensland University, Rockhampton, QLD 4701, Australia

3. Centre of Railway Engineering, School of Engineering and Technology, Central Queensland University, Rockhampton, QLD 4701, Australia

Abstract

Chinese calligraphy, revered globally for its therapeutic and mindfulness benefits, encompasses styles such as regular (Kai Shu), running (Xing Shu), official (Li Shu), and cursive (Cao Shu) scripts. Beginners often start with the regular script, advancing to more intricate styles like cursive. Each style, marked by unique historical calligraphy contributions, requires learners to discern distinct nuances. The integration of AI in calligraphy analysis, collection, recognition, and classification is pivotal. This study introduces an innovative convolutional neural network (CNN) architecture, pioneering the application of CNN in the classification of Chinese calligraphy. Focusing on the four principal calligraphy styles from the Tang dynasty (690–907 A.D.), this research spotlights the era when the traditional regular script font (Kai Shu) was refined. A comprehensive dataset of 8282 samples from these calligraphers, representing the zenith of regular style, was compiled for CNN training and testing. The model distinguishes personal styles for classification, showing superior performance over existing networks. Achieving 89.5–96.2% accuracy in calligraphy classification, our approach underscores the significance of CNN in the categorization of both font and artistic styles. This research paves the way for advanced studies in Chinese calligraphy and its cultural implications.

Funder

CQUniversity Research Internal Grants

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference39 articles.

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5. Liu, S. (2003). Full Colour Art History of Chinese Calligraphy, Ningxia People’s Publishing House. [1st ed.].

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