Segmentation and Recognition for Historical Tibetan Document Images
| Autor: | Long-Long Ma, Xiqun Zhang, Yanxing Li, Congjun Long, Quanchao Zhao, Lijuan Duan |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
touching character string segmentation
General Computer Science Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology computer.software_genre Graph model Document segmentation Font 0202 electrical engineering electronic engineering information engineering General Materials Science Segmentation Electrical and Electronic Engineering Historical Tibetan document layout segmentation Projection (set theory) Digitization computer.programming_language Block (data storage) business.industry General Engineering text-line segmentation 020206 networking & telecommunications PEARL (programming language) block projection ComputingMethodologies_DOCUMENTANDTEXTPROCESSING 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering Artificial intelligence business lcsh:TK1-9971 computer Natural language processing |
| Zdroj: | IEEE Access, Vol 8, Pp 52641-52651 (2020) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2020.2975023 |
| Popis: | As a shining pearl in traditional Tibetan culture, historical Tibetan documents have received extensive attention from historians, linguists and Buddhist scholars. These documents are converted into digital form using Tibetan document segmentation and recognition methods. The document digitization is of great significance for the research, protection and inheritance of Tibetan history. This paper proposes an overall segmentation and recognition framework for historical Tibetan document images. Firstly, the historical Tibetan document image is preprocessed to correct imbalanced illumination, tilt and noises, and is further transformed into the binarized image. Secondly, we propose a layout segmentation method based on block projection to segment Tibetan document images into texts, lines and frames. Thirdly, in order to solve the problems of touching strokes between text-lines and curvilinear text-lines, we present a text-line segmentation method based on graph model for historical Tibetan text-line segmentation. Lastly, we present a touching segmentation method to segment touching Tibetan character string, and then recognize Tibetan characters. Experimental results show our proposed methods on layout segmentation, text-line segmentation and touching character string segmentation, achieve the satisfactory performance. The proposed methods can also be applied to other fonts in Tibetan font family. |
| Databáze: | OpenAIRE |
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