Table Structure Recognition Method Based on Two-stage Deep Learning
In view of the difficulties of table structures recognition in images,such as numerous table styles and different image quality,a two-stage deep learning framework integrating table lines and text block information was proposed to realize the recognition of complex table structures with few lines.Firstly,the residual structure was introduced into the U-Net semantic segmentation network to enhance the network transmission ability of table line information and complete the recognition of table line.Then,the text block location information was added to improve the ability of the model to recognize wirelessor less linear table structures.The TEDS(tree-edit-distance similarity)score of this method was 95.95 on PubTabNet dataset.The experimental results suggested that the proposed method performed well in recognition of few line tables or wireless tables,and could efficiently and accurately recognize the complex structure tables with merged cells.