Character Detection and Segmentation of Historical Uchen Tibetan Documents in Complex Situations
Open Access
- 15 February 2022
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Access
- Vol. 10, 25376-25391
Abstract
Tibetan is a low-resource language, and Tibetan culture carried by historical Tibetan documents is an important part of Chinese civilization. The study of historical Tibetan documents is of great significance to the protection of Tibetan culture and the promotion of Chinese culture. Character segmentation is an important step in image analysis and recognition of historical Tibetan documents. However, the following three challenges prevent solving problems of character segmentation in historical Tibetan documents: 1) the text lines have different degrees of tilt and twist; 2) there are many complex situations such as overlapping, crossing, touching and breaking character strokes; and 3) these documents are written by different people with different stroke styles. To resolve these problems, we propose a character segmentation method based on key feature information for historical Tibetan documents. The proposed method consists of three parts: 1) projection and syllable point location information are used to shorten the text lines of historical Tibetan documents and establish a character block database; 2) the local baseline of the character block is detected by using the location information of syllable points or combined with horizontal projection and straight line detection, and the character block is divided into two areas above and below the baseline, and different segmentation methods are adopted; and 3) in view of the large difference in stroke styles, three stroke attribution distances are used to complete the attribution. The experimental results show that the method proposed in this paper can effectively solve the problem of character segmentation of historical Tibetan documents and achieve a better character segmentation effect, which also provides a reference for the relevant document character segmentation.Keywords
Funding Information
- National Natural Science Foundation of China (61772430, 62166036)
- program for Leading Talent of State Ethnic Affairs Commission
- Program for Innovative Research Team of SEAC
- Gansu Provincial First-Class Discipline Program of Northwest Minzu University through the “Innovation Star” Project of Excellent Postgraduates of Gansu Provincial Department of Education (2021CXZX-663)
- Science and Technology Research Program of Chongqing Education Commission (KJQN202101608)
- Research Program of Chongqing University of Education (KY202118C)
- Key Projects of Natural Science Research in Anhui Colleges and Universities (KJ2020ZD46)
This publication has 30 references indexed in Scilit:
- A Text-Line Segmentation Method for Historical Tibetan Documents Based on Baseline Detection2017
- Text extraction method for historical Tibetan document images based on block projectionsOptoelectronics Letters, 2017
- A novel drop-fall algorithm based on digital features for touching digit segmentation2016
- Enhanced Character Segmentation for Format-Free Japanese Text Recognition2016
- Graph Model Optimization Based Historical Chinese Character Segmentation Method2014
- An over-segmentation method for single-touching Chinese handwriting with learning-based filteringInternational Journal on Document Analysis and Recognition (IJDAR), 2013
- Recognition of Tibetan wood block prints with generalized hidden Markov and kernelized modified quadratic distance function2011
- Segmentation of numeric strings1995
- Extraction of Characteristic Features in Tibetan Wood-block EditionsJournal of Indian and Buddhist Studies (Indogaku Bukkyogaku Kenkyu), 1994
- Automatic Character Recognition for Tibetan ScriptJournal of Indian and Buddhist Studies (Indogaku Bukkyogaku Kenkyu), 1991