[1]吴燕如,珠 杰,管美静.基于深度学习的藏文现代印刷物版面检测技术研究[J].南京师范大学学报(工程技术版),2021,21(01):044-48.[doi:10.3969/j.issn.1672-1292.2021.01.007]
　Wu Yanru,Zhu Jie,Guan Meijing.Research on Layout Inspection Technology of ModernTibetan Prints Based on Deep Learning[J].Journal of Nanjing Normal University(Engineering and Technology),2021,21(01):044-48.[doi:10.3969/j.issn.1672-1292.2021.01.007]
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基于深度学习的藏文现代印刷物版面检测技术研究
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南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
21卷
期数:
2021年01期
页码:
044-48
栏目:
计算机科学与技术
出版日期:
2021-03-15

文章信息/Info

Title:
Research on Layout Inspection Technology of ModernTibetan Prints Based on Deep Learning
文章编号:
1672-1292(2021)01-0044-05
作者:
吴燕如1; 2; 珠 杰1; 2; 管美静1; 2
(1.西藏大学信息科学技术学院,西藏 拉萨 850000)(2.藏文信息技术国家地方联合中心,西藏 拉萨 850000)
Author(s):
Wu Yanru1; 2; Zhu Jie1; 2; Guan Meijing1; 2
(1.School of Information Science and Technology,Tibet University,Lhasa 850000,China)(2.National and Local Joint Center for Tibetan Information Technology,Lhasa 850000,China)
关键词:
深度学习; 藏文现代印刷物; Faster R-CNN; 版面检测
Keywords:
deep learning; modern Tibetan prints; Faster R-CNN; layout detection
分类号:
TP391
DOI:
10.3969/j.issn.1672-1292.2021.01.007
文献标志码:
A
摘要:
针对藏文现代图书版面中的文本行分布不均匀、现代藏文字体差异较大的问题,提出了一种基于Faster R-CNN的版面文本行检测算法. 通过在整理标注的数据集上训练,用ResNet-50网络提取出藏文现代图书版面特征信息. 为了有效提高模型的泛化能力,在COCO数据集下的网络模型中进行迁移学习. 实验结果表明,该方法可对藏文现代印刷物的版面实现文本行的定位,检测准确率为83%,召回率为95%,明显提高了版面检测的精确度.
Abstract:
Aimed at the uneven distribution of text lines in the layout of modern Tibetan books and the large differences in modern Tibetan fonts,a layout text line detection algorithm based on Faster R-CNN is proposed. By training on collated and labeled data set,we use the ResNet-50 network to extract the feature information of the Tibetan modern book layout. In order to effectively improve the generalization ability of the model,transfer learning is performed in the network model under the COCO dataset. The experimental results show that this method can realize text line positioning on the layout of modern Tibetan printed materials,with a detection accuracy rate of 83% and the recall rate of 95%,which significantly improves the accuracy of layout detection.

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备注/Memo

备注/Memo:
收稿日期:2020-08-08.
基金项目:西藏大学研究生“高水平人才培养计划”项目(2017-GSP-131)、西藏自治区高等教育教学改革研究重点项目、多学科融合的新工科创新创业教育体系研究项目、藏语文传承与发展之藏汉双向机器翻译平台建设项目、计算机及藏文信息技术国家团队及重点实验室建设项目(藏大财指[2018]81号)、国家重点研发计划重点专项(2017YFB140220).
通讯作者:珠杰,博士,教授,博士生导师,研究方向:藏文信息处理、数据挖掘. E-mail:790139756@qq.com
更新日期/Last Update: 2021-03-15