A Model for Detecting and Merging Vertically Spanned Table Cells in Plain Text Documents

Authors:
Vanessa Long;Robert Dale;Steve Cassidy
Affiliations:
Macquarie University Sydney, Australia;Macquarie University Sydney, Australia;Macquarie University Sydney, Australia
Venue:
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Year:
2005

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Abstract

A spanned cell in a table is a single, complete unit that physically occupies multiple columns and/or multiple rows. Spanned cells are common in tables, and they are a signifi- cant cause of error in the extraction of tables from free text documents. In this paper, we present a model for the detection and merging of vertically spanned cells for tables presented in plain text documents. Our model and algorithm are based purely on the layout features of the tables, and they require no semantic understanding of the documents. When tested on the 98 tables appearing in 40 randomly selected documents from a corpus of company announcements from the Australian Stock Exchange (ASX), our algorithm achieves an accuracy of 86.79% in detecting and merging vertically spanned cells.