Aiming at the problems of many seals, shallow impressions and low accuracy of seal identification, a modified YOLOv5 seal identification algorithm is proposed. The algorithm improvement is divided into two aspects. First, CBAM attention module is introduced to improve the feature extraction ability of the model. Secondly, and EIoU Loss is introduced to replace the CIOU Loss boundary box regression loss function in the algorithm, which effectively solves the aspect ratio described as the relative value, which is a certain fuzzy problem. Experiments show that the improved algorithm′s seal recognition F1 score has reached 0.95, which is a 2% improvement compared to the original algorithm. Finally, to use the seal to verify the effectiveness of the model, the improved YOLOv5 model is called in the digital archive processing system, and the results show that the improved algorithm can run stably in the system.