Automatic Table ground truth generation and a background-analysis-based table structure extraction method

Yalin Wang, Ihsin T. Phillips, Robert Haralick

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

36 Scopus citations

Abstract

In this paper, we first describe an automatic table ground truth generation system which can efficiently generate a large amount of accurate table ground truth suitable for the development of table detection algorithms. Then a novel background-analysis-based, coarse-to-fine table identification algorithm and an X-Y cut table decomposition algorithm are described. We discuss an experimental protocol to evaluate the table detection algorithms. For a total of 1,125 document pages having 518 table entities and a total of 10,941 cell entities, our table detection algorithm takes line, word segmentation results as input and obtains around 90% cell correct detection rates.

Original languageEnglish (US)
Title of host publicationProceedings - 6th International Conference on Document Analysis and Recognition, ICDAR 2001
PublisherIEEE Computer Society
Pages528-532
Number of pages5
ISBN (Electronic)0769512631, 0769512631, 0769512631
DOIs
StatePublished - Jan 1 2001
Externally publishedYes
Event6th International Conference on Document Analysis and Recognition, ICDAR 2001 - Seattle, United States
Duration: Sep 10 2001Sep 13 2001

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume2001-January
ISSN (Print)1520-5363

Other

Other6th International Conference on Document Analysis and Recognition, ICDAR 2001
CountryUnited States
CitySeattle
Period9/10/019/13/01

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Wang, Y., Phillips, I. T., & Haralick, R. (2001). Automatic Table ground truth generation and a background-analysis-based table structure extraction method. In Proceedings - 6th International Conference on Document Analysis and Recognition, ICDAR 2001 (pp. 528-532). [953845] (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR; Vol. 2001-January). IEEE Computer Society. https://doi.org/10.1109/ICDAR.2001.953845