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作者:

Li, Yanxing (Li, Yanxing.) | Ma, Longlong (Ma, Longlong.) | Duan, Lijuan (Duan, Lijuan.) (学者:段立娟) | Wu, Jian (Wu, Jian.)

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CPCI-S EI Scopus

摘要:

Text-line segmentation is an important task in the historical Tibetan document recognition. Historical Tibetan document images usually contain touching or overlapping characters between consecutive text-lines, making text-line segmentation a difficult task. In this paper, we present a text-line segmentation method based on baseline detection. The initial positions for the baseline of each line are obtained by template matching, pruning algorithms and closing operation. The baseline is estimated using dynamic tracing within pixel points of each line and the context information between pixel points. The overlapping or touching areas are cut by finding the minimum width stroke. Finally, text-lines are extracted based on the estimated baseline and the cut position of touching area. The proposed algorithm has been evaluated on the dataset of historical Tibetan document images. Experimental result shows the effectiveness of the proposed method.

关键词:

Baseline detection Historical Tibetan document Text-line segmentation

作者机构:

  • [ 1 ] [Li, Yanxing]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 2 ] [Duan, Lijuan]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 3 ] [Wu, Jian]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 4 ] [Li, Yanxing]Beijing Key Lab Trusted Comp, Beijing, Peoples R China
  • [ 5 ] [Ma, Longlong]Chinese Acad Sci, Inst Software, Chinese Informat Proc Lab, Beijing, Peoples R China
  • [ 6 ] [Wu, Jian]Chinese Acad Sci, Inst Software, Chinese Informat Proc Lab, Beijing, Peoples R China
  • [ 7 ] [Duan, Lijuan]Beijing Key Lab Integrat & Anal Large Scale Strea, Beijing, Peoples R China

通讯作者信息:

  • 段立娟

    [Duan, Lijuan]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China;;[Duan, Lijuan]Beijing Key Lab Integrat & Anal Large Scale Strea, Beijing, Peoples R China

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来源 :

COMPUTER VISION, PT I

ISSN: 1865-0929

年份: 2017

卷: 771

页码: 356-367

语种: 英文

被引次数:

WoS核心集被引频次: 7

SCOPUS被引频次: 10

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

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