LAUSR

To solve the component segmentation problem caused by the sticking and overlapping of parts in incoherent handwritten calligraphy characters, we propose a Chinese character part segmentation method based on Faster RCNN. The method utilizes the advantages of Faster RCNN on multi-scale and small targets to solve difficult problems in component segmentation. The hierarchical features of the components were used in our proposed method to identify each layer of the Chinese character structure to obtain the components. Qualitative and quantitative calculations were used to test the segmentation effect of the proposed method. The experimental results demonstrate the accurate segmentation effectiveness of our method for adhering and overlapping components. In addition, these components could be retrieved accurately in the retrieval system, and the mean Average Precision of the top 30 retrieval results reached 95.7%. A better retrieval accuracy reflects a better segmentation effect from the side, which proves the effectiveness of the proposed method.