Offline Printed Tai Le Character Recognition Using VGGNET

被引：1
|
作者：
Zhao, Jingying [1 ,2 ]
Guo, Hai [1 ]
Song, Yifan [1 ]
Dai, Ling [1 ]
Liu, Yifan [1 ]
机构：
[1] Dalian Minzu Univ, Coll Comp Sci & Engn, Dalian, Peoples R China
[2] Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian, Peoples R China
来源：
2021 IEEE INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND SOFTWARE ENGINEERING (ICICSE 2021) | 2021年
关键词：
Tai Le; optical character recognition; image digital processing; VGGNET;
D O I：
10.1109/ICICSE52190.2021.9404133
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
It is a difficult problem to recognize the Tai Le characters, since they are close in shape and high in proportion. This paper constructs an offline printed Tai Le recognition model based on VGGNET. First, the database YDH2019.1 containing 135000 printed Tai Le character images and 35 types of Tai Le characters is built. Then, YDH2019.1 is preprocessed by noise reduction and normalization, and VGG16 is used as the classifier of the model. The results show that the Precision of the recognition model is 0.999943, recall is 0.999943, and fl-score is 0.999943, which can effectively recognize the offline printed Tai Le characters.
引用
收藏
页码：117 / 121
页数：5
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