Chinese cursive character detection method

Abstract

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.