Research on automatic segmentation and recognition of single characters of original topography in intelligent recognition of oracle bone inscriptions

Intelligent recognition technology, as an important technical tool, has played a significant role in many fields. In this paper, for the issue of oracle bone image processing, we first conducted image pre-processing, including size adjustment, normalization, and data enhancement steps, to improve image quality and highlight the oracle bone information. Then, the YOLOv5 model is utilized for oracle bone image segmentation, achieving high recognition accuracy after 50 epochs of training. Finally, the model was employed to automatically segment the original oracle bone topography images for individual characters, with an average processing time of only 810.8ms, demonstrating efficient processing speed. In total, 1447 oracle bones were automatically detected and segmented, achieving a high level of accuracy.