A cell-detection-based table-structure recognition method

Manabu Ohta, Ryoya Yamada, Teruhito Kanazawa, Atsuhiro Takasu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)


If tables are automatically recognized to extract the numerical values in them, digital documents containing such tables can be augmented with graphs generated using the recognized tables. In this paper, we propose a cell-detection-based table-structure recognition method for such automatic graph generation from tables. In detecting cells in a table, ruled lines are crucial but do not necessarily surround all cells. We therefore propose a method to detect cells by estimating implicit ruled lines, where necessary, to recognize the table structure. We demonstrate the effectiveness of the proposed method by experiments using the ICDAR 2013 table competition dataset.

Original languageEnglish
Title of host publicationProceedings of the ACM Symposium on Document Engineering, DocEng 2019
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450368872
Publication statusPublished - Sept 23 2019
Event19th ACM Symposium on Document Engineering, DocEng 2019 - Berlin, Germany
Duration: Sept 23 2019Sept 26 2019

Publication series

NameProceedings of the ACM Symposium on Document Engineering, DocEng 2019


Conference19th ACM Symposium on Document Engineering, DocEng 2019


  • PDF
  • Table-structure analysis
  • Table-structure recognition
  • XML

ASJC Scopus subject areas

  • Software
  • Information Systems


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