DeepJiandu Dataset for Character Detection and Recognition on Jiandu Manuscript
Yiran Liu, Qiang Zhang, Ying Qi, Teng Wan, Defang Zhang, Yutong Li, Xin Zhang, L. Ma, Qiuyue Ruan, Huanting Guo, Yingchun Li, Xinyue Miao, Wenjun Xiao, Yongbo Li, Jiang Yuan, Shanxiong Chen
Abstract
In ancient China, bamboo and wooden slips, known as "Jiandu", were the primary mediums for recording historical events before the invention of paper. These artifacts are rich in historical data and cultural significance. Accurate identification of characters on Jiandu is essential for deciphering the historical narratives they contain and plays a vital role in processing Jiandu manuscripts. In this study, we introduce the DeepJiandu dataset, specifically designed for the detection and recognition of Jiandu characters. The dataset comprises 7,416 images annotated with 99,852 characters across 2,242 categories. It addresses a variety of complex challenges encountered in Jiandu character recognition, including character degradation, diverse layouts, and variable forms and shapes. The authenticity and reliability of the DeepJiandu dataset render it an effective tool for training and evaluating models geared towards Jiandu character recognition, thereby streamlining the research and organization of Jiandu information.