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Proceedings Paper

Table structure recognition and its evaluation
Author(s): Jianying Hu; Ramanujan S. Kashi; Daniel P. Lopresti; Gordon Wilfong
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Paper Abstract

Tables are an important means for communicating information in written media, and understanding such tables is a challenging problem in document layout analysis. In this paper we describe a general solution to the problem of recognizing the structure of a detected table region. First hierarchial clustering is used to identify columns and then spatial and lexical criteria to classify headers. We also address the problem of evaluating table structure recognition. Our model is based on a directed acyclic attribute graph, or table DAG. We describe a new paradigm, 'random graph probing,' for comparing the results returned by the recognition system and the representation created during ground-truthing. Probing is in fact a general concept that could be applied to other document recognition tasks and perhaps even other computer vision problems as well.

Paper Details

Date Published: 21 December 2000
PDF: 12 pages
Proc. SPIE 4307, Document Recognition and Retrieval VIII, (21 December 2000); doi: 10.1117/12.410859
Show Author Affiliations
Jianying Hu, Avaya Labs. Research (United States)
Ramanujan S. Kashi, Avaya Labs. Research (United States)
Daniel P. Lopresti, Lucent Technologies/Bell Labs. (United States)
Gordon Wilfong, Lucent Technologies/Bell Labs. (United States)


Published in SPIE Proceedings Vol. 4307:
Document Recognition and Retrieval VIII
Paul B. Kantor; Daniel P. Lopresti; Jiangying Zhou, Editor(s)

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