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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Main Authors: Longlong Ma, Congjun Long, Lijuan Duan, Xiqun Zhang, Yanxing Li, Quanchao Zhao
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
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.
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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
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AT lijuanduan segmentationandrecognitionforhistoricaltibetandocumentimages
AT xiqunzhang segmentationandrecognitionforhistoricaltibetandocumentimages
AT yanxingli segmentationandrecognitionforhistoricaltibetandocumentimages
AT quanchaozhao segmentationandrecognitionforhistoricaltibetandocumentimages