Document Analysis and Recognition

, Volume 7, Issue 1, pp 1–16

A survey of table recognition

Models, observations, transformations, and inferences
  • Richard Zanibbi
  • Dorothea Blostein
  • James R. Cordy
Article

DOI: 10.1007/s10032-004-0120-9

Cite this article as:
Zanibbi, R., Blostein, D. & Cordy, J.R. IJDAR (2004) 7: 1. doi:10.1007/s10032-004-0120-9

Abstract.

Table characteristics vary widely. Consequently, a great variety of computational approaches have been applied to table recognition. In this survey, the table recognition literature is presented as an interaction of table models, observations, transformations, and inferences. A table model defines the physical and logical structure of tables; the model is used to detect tables and to analyze and decompose the detected tables. Observations perform feature measurements and data lookup, transformations alter or restructure data, and inferences generate and test hypotheses. This presentation clarifies both the decisions made by a table recognizer and the assumptions and inferencing techniques that underlie these decisions.

Keywords:

Table recognition Modeling table structure Performance evaluation Information retrieval 

Copyright information

© Springer-Verlag Berlin/Heidelberg 2004

Authors and Affiliations

  • Richard Zanibbi
    • 1
  • Dorothea Blostein
    • 1
  • James R. Cordy
    • 1
  1. 1.School of ComputingQueen’s UniversityKingstonCanada