Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)

Chinese Font Recognition Based on Convolution Neural Network

Authors
Yifan Chang
Corresponding Author
Yifan Chang
Available Online May 2018.
DOI
https://doi.org/10.2991/amcce-18.2018.97How to use a DOI?
Keywords
Font Recognition; Image Processing; CNN
Abstract
In the traditional OCR text recognition system, recognition rate is low with many errors.Also, it can not effectively identify the different text fonts. It’s a long-standing problem. Modern text recognition system should be for different fonts within accuracy to identify the text and font information. The traditional methods are mostly based on feature extraction, including local features extraction and global features extraction. Proposes a Convolution Neural Network[1] based on deep learning to deal with Chinese font recognition. Compared with the previous methods, this method has high recognition rate and high speed and is suitable for complex applications.
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Proceedings
2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
Part of series
Advances in Engineering Research
Publication Date
May 2018
ISBN
978-94-6252-508-5
ISSN
2352-5401
DOI
https://doi.org/10.2991/amcce-18.2018.97How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yifan Chang
PY  - 2018/05
DA  - 2018/05
TI  - Chinese Font Recognition Based on Convolution Neural Network
BT  - 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.97
DO  - https://doi.org/10.2991/amcce-18.2018.97
ID  - Chang2018/05
ER  -