Enhancing Chinese Font Recognition with Convolutional Neural Networks

With more and more styles of fonts, young people are keen to use distinctive fonts to show their individuality. The purpose of this paper is to study Chinese font classification recognition to enable people to handle fonts more effectively. For this purpose, Nankai Chinese font style dataset is used...

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Bibliographic Details
Published in2023 International Conference on Networks, Communications and Intelligent Computing (NCIC) pp. 291 - 295
Main Author Li, Mengyuan
Format Conference Proceeding
LanguageEnglish
Published IEEE 17.11.2023
Subjects
Accuracy Optimization
Character recognition
Chinese Character Dataset
Computational modeling
Convolutional Neural Network
Convolutional neural networks
Data models
Font Classification
Normalized Central Moment Features
Optimization
Testing
Training
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Summary:With more and more styles of fonts, young people are keen to use distinctive fonts to show their individuality. The purpose of this paper is to study Chinese font classification recognition to enable people to handle fonts more effectively. For this purpose, Nankai Chinese font style dataset is used for subsequent training and testing. The dataset was processed by normalizing the central moment features. The data was imported into the Sequential model of keras, and the accuracy of font classification was obtained after convolutional processing as 94.67%. The accuracy and running speed of the font recognition model in this study are excellent. The results show that this model is able to solve problem font recognition outstandingly after learning and training.
DOI:10.1109/NCIC61838.2023.00055