Chinese ancient book character recognition method, Chinese ancient book character segmentation, layout reconstruction method, medium and equipment

Abstract

The invention discloses a Chinese ancient book character recognition method, a Chinese ancient book character segmentation, a layout reconstruction method, a medium and equipment, and the Chinese ancient book character recognition method comprises the steps: firstly obtaining a Chinese ancient book document image marked with a character bounding box and a character category, and taking the image as an original training sample; acquiring an annotation file of the original training sample; randomly selecting a plurality of original training samples, and processing the original training samples to obtain new training samples: processing the original training samples and the new training samples in an online random cutting mode to obtain a training sample set; training a character level detection classification model through training samples in the training sample set; and inputting a Chinese ancient book document image of which characters are to be recognized into the character level detection classification model to obtain a prediction bounding box and a prediction category of each character of the Chinese ancient book document image. According to the method, common characters can be recognized, some uncommon special characters in the ancient books can be recognized very accurately, and the problems of misjudgment, omission and the like existing in ancient book document recognition in the prior art are solved.

Description

technical field [0001] The invention relates to the technical field of ancient Chinese books research, in particular to a method, medium and equipment for character recognition, grouping and layout reconstruction of ancient Chinese books. Background technique [0002] With the research and development of deep learning, image text detection and recognition technology based on computer vision is playing an increasingly important role in daily life, business activities and scientific research, and has made good progress. The research results involve document recognition , bill recognition and specific scene text recognition. However, the existing research is only for text images with clear handwriting, obvious background contrast, and limited character categories. The distribution of characters follows the modern typesetting style from left to right and top to bottom. There are deficiencies in the research work on the recognition of ancient book documents that follow the arran...

AI Technical Summary

Problems solved by technology

However, there are special elements such as icons, seals, and double-column notes in Chinese ancient book documents. Traditional text line detection algorithms or only focus on simple layouts such as single-line text are not suitable for ancient book documents with complex layout structures and diverse contents.

At the same time, there are handwritten, variant or uncommon fonts in Chinese ancient book documents, and traditional algorithms that focus on common printed Chinese character recognition can only deal with limited types of characters, and cannot accurately identify these uncommon special characters. There are disadvantages such as misjudgment and omission in the identification of ancient book documents

In addition, there is currently a lack of ancient book document datasets with a wide coverage of character categories and various font styles, and the distribution of character categories in the annotation data of existing ancient book document image datasets is uneven

Images