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Proceedings Paper

Medium-independent table detection
Author(s): Jianying Hu; Ramanujan S. Kashi; Daniel P. Lopresti; Gordon Wilfong
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Paper Abstract

An important step towards the goal of table understanding is a method for reliable table detection. This paper describes a general solution for detecting tables based on computing an optimal partitioning of a document into some number of tables. A dynamic programming algorithm is given to solve the resulting optimization problem. This high-level framework is independent of any particular table quality measure and independent of the document medium. Moreover, it does not rely on the presence of ruling lines or other table delimiters. We also present table quality measures based on white space correlation and vertical connected component analysis. These measures can be applied equally well to ASCII text and scanned images. We report on some preliminary experiments using this method to detect tables in both ASCII text and scanned images, yielding promising results. We present detailed evaluation of these results using three different criteria which by themselves pose interesting research questions.

Paper Details

Date Published: 22 December 1999
PDF: 12 pages
Proc. SPIE 3967, Document Recognition and Retrieval VII, (22 December 1999); doi: 10.1117/12.373506
Show Author Affiliations
Jianying Hu, Lucent Technologies/Bell Labs. (United States)
Ramanujan S. Kashi, Lucent Technologies/Bell Labs. (United States)
Daniel P. Lopresti, Lucent Technologies/Bell Labs. (United States)
Gordon Wilfong, Lucent Technologies/Bell Labs. (United States)


Published in SPIE Proceedings Vol. 3967:
Document Recognition and Retrieval VII
Daniel P. Lopresti; Jiangying Zhou, Editor(s)

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