Segmentation and Recognition for Historical Tibetan Document Images
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 i...
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Format: | Article |
Language: | English |
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IEEE
2020-01-01
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Series: | IEEE Access |
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Online Access: | https://ieeexplore.ieee.org/document/9003213/ |
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author | Longlong Ma Congjun Long Lijuan Duan Xiqun Zhang Yanxing Li Quanchao Zhao |
author_facet | Longlong Ma Congjun Long Lijuan Duan Xiqun Zhang Yanxing Li Quanchao Zhao |
author_sort | Longlong Ma |
collection | DOAJ |
description | 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. |
first_indexed | 2024-12-10T11:20:09Z |
format | Article |
id | doaj.art-ad32df7e00d449df9601ec012b20dff2 |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-12-10T11:20:09Z |
publishDate | 2020-01-01 |
publisher | IEEE |
record_format | Article |
series | IEEE Access |
spelling | doaj.art-ad32df7e00d449df9601ec012b20dff22022-12-22T01:51:00ZengIEEEIEEE Access2169-35362020-01-018526415265110.1109/ACCESS.2020.29750239003213Segmentation and Recognition for Historical Tibetan Document ImagesLonglong Ma0https://orcid.org/0000-0002-7568-5003Congjun Long1Lijuan Duan2https://orcid.org/0000-0001-9836-482XXiqun Zhang3Yanxing Li4Quanchao Zhao5Institute of Software, Chinese Academy of Sciences, Beijing, ChinaInstitute of Ethnology and Anthropology, Chinese Academy of Social Sciences, Beijing, ChinaFaculty of Information Technology, Beijing University of Technology, Beijing, ChinaFaculty of Information Technology, Beijing University of Technology, Beijing, ChinaFaculty of Information Technology, Beijing University of Technology, Beijing, ChinaFaculty of Information Technology, Beijing University of Technology, Beijing, ChinaAs 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.https://ieeexplore.ieee.org/document/9003213/Historical Tibetan documentlayout segmentationtext-line segmentationtouching character string segmentationblock projection |
spellingShingle | Longlong Ma Congjun Long Lijuan Duan Xiqun Zhang Yanxing Li Quanchao Zhao Segmentation and Recognition for Historical Tibetan Document Images IEEE Access Historical Tibetan document layout segmentation text-line segmentation touching character string segmentation block projection |
title | Segmentation and Recognition for Historical Tibetan Document Images |
title_full | Segmentation and Recognition for Historical Tibetan Document Images |
title_fullStr | Segmentation and Recognition for Historical Tibetan Document Images |
title_full_unstemmed | Segmentation and Recognition for Historical Tibetan Document Images |
title_short | Segmentation and Recognition for Historical Tibetan Document Images |
title_sort | segmentation and recognition for historical tibetan document images |
topic | Historical Tibetan document layout segmentation text-line segmentation touching character string segmentation block projection |
url | https://ieeexplore.ieee.org/document/9003213/ |
work_keys_str_mv | AT longlongma segmentationandrecognitionforhistoricaltibetandocumentimages AT congjunlong segmentationandrecognitionforhistoricaltibetandocumentimages AT lijuanduan segmentationandrecognitionforhistoricaltibetandocumentimages AT xiqunzhang segmentationandrecognitionforhistoricaltibetandocumentimages AT yanxingli segmentationandrecognitionforhistoricaltibetandocumentimages AT quanchaozhao segmentationandrecognitionforhistoricaltibetandocumentimages |