Chinese cursive character detection method

被引:3
|
作者
Qin, Xiao [1 ]
Jiang, Jianhui [1 ]
Fan, Wei [1 ]
Yuan, Changan [1 ]
机构
[1] Nanning Normal Univ, Sch Comp & Informat Engn, Nanning 530001, Peoples R China
来源
JOURNAL OF ENGINEERING-JOE | 2020年 / 2020卷 / 13期
基金
中国国家自然科学基金;
关键词
feature extraction; handwritten character recognition; text analysis; text detection; history; art; natural languages; SE-seglink method; Chinese cursive character detection method; Chinese cursive script; distinctive calligraphy art; connected writing; text recognition; cursive image dataset; continuous strokes text; image feature extraction; traditional cultures; ICDAR2015 benchmark image dataset;
D O I
10.1049/joe.2019.1208
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Chinese is a widely used language in the world. Chinese cursive script is one of the most distinctive calligraphy art and traditional cultures of China. However, for its connected writing, there is a lack of research on text recognition for cursive images. Here, the authors construct a small cursive image dataset named as Chinese Cursive and there are 523 images in this dataset. It contains continuous strokes text, recognises difficulty etc. Each cursive character is corresponded to a label. The authors proposed a cursive detection method named as SE-seglink for the dataset. The SE-seglink further enhances the image feature extraction. Compared to the existing methods, the SE-seglink performs better in recognising cursive scripts and improves the precision of text detection in cursive images. After multiple sets of comparative experiments, the effectiveness of the SE-seglink method was evaluated by the experiment on the benchmark image dataset ICDAR2015.
引用
收藏
页码:626 / 629
页数:4
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