A Constraint-based Approach to Table Structure Derivation

I
ICDAR
2003
Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2
Abstract - A Constraint-based Approach to Table Structure Derivation

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Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2

Edinburgh, Scotland

August 03-August 06

ISBN: 0-7695-1960-1

	ASCII Text	x
	Matthew Hurst, "A Constraint-based Approach to Table Structure Derivation," Document Analysis and Recognition, International Conference on, vol. 2, pp. 911, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2, 2003.

	BibTex	x
	@article{ 10.1109/ICDAR.2003.1227792, author = {Matthew Hurst}, title = {A Constraint-based Approach to Table Structure Derivation}, journal ={Document Analysis and Recognition, International Conference on}, volume = {2}, year = {2003}, isbn = {0-7695-1960-1}, pages = {911}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227792}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Document Analysis and Recognition, International Conference on TI - A Constraint-based Approach to Table Structure Derivation SN - 0-7695-1960-1 SP EP A1 - Matthew Hurst, PY - 2003 KW - null VL - 2 JA - Document Analysis and Recognition, International Conference on ER -

Matthew Hurst, Intelliseek, Inc.

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227792

This paper presents an approach to deriving an abstract geometric model of a table from a physical representation. The technique developed uses a graph of constraints between cells which must be satisfied in order to determine their relative horizontal and vertical position. The method is evaluated with a test set of tables drawn from US Securities and Exchange Commission (SEC) filings.

Citation:

Matthew Hurst, "A Constraint-based Approach to Table Structure Derivation," icdar, vol. 2, pp.911, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2, 2003

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