This paper proposes a post-OCR method of multi-model ensemble, which uses a unique layout analysis and alignment algorithms, and integrate different types of deep learning models, such as the full-page character detection model, character recognition model, line recognition model and language pre-training model, and achieves effects beyond a single model. The full-text error rate reaches 1.64%, which is only 23% of the average error rate of a single model. In various conventional ancient book layout scenarios, this method has good generalization.
