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Design and Application of Clerical Style Recognition System Based on Data Mining Algorithm

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Publicado en:International Journal of Information System Modeling and Design vol. 16, no. 1 (2025), p. 1-18
Autor principal: Jiang, Feifei
Otros Autores: Ke, Chenghu, Zhong, Chenchen, Zhang, Xiaoling
Publicado:
IGI Global
Materias:
Calligraphy
Digital imaging
Data mining
Artificial intelligence
Pattern analysis
Computer vision
Character recognition
Algorithms
Information systems
Methods
Cluster analysis
Automation
Clustering
Digital computers
Handwriting
Digitization
Pattern recognition
Handwriting recognition
High definition
Acceso en línea:Citation/Abstract
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Resumen:With the advancements in high-definition imaging and parallel computing hardware, the analysis of massive visual data has become a key focus in pattern recognition and artificial intelligence. Chinese calligraphy, an integral part of traditional culture, has seen digitization of numerous works stored in digital libraries. However, current automatic calligraphy character recognition technology is limited, necessitating the development of efficient computer vision methods for recognizing calligraphy styles. Data mining, crucial in artificial intelligence, involves extracting valuable knowledge from vast and noisy datasets. Recent simulation results show promising recognition rates for Chinese text images, with an average recognition time of 5 seconds per 100 words. This system significantly improves handwriting recognition accuracy compared to existing algorithms, though further refinement and expansion are needed for optimal functionality.
ISSN:1947-8186
1947-8194
DOI:10.4018/IJISMD.365344
Fuente:Engineering Database