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ICDAR 2013 Table Competition

Max Göbel‚ Tamir Hassan‚ Linda Oro and Giorgio Orsi

Abstract

Table understanding is a well studied problem in document analysis, and many academic and commercial approaches have been developed to recognize tables in several document formats, including plain text, scanned page images and born-digital, object-based formats such as PDF. Despite the abundance of these techniques, an objective comparison of their performance is still missing. The Table Competition held in the context of ICDAR 2013 is our first attempt at objectively evaluating these techniques against each other in a standardized way, across several input formats. The competition independently addresses three problems: (i) table location, (ii) table structure recognition, and (iii) these two tasks combined. We received results from seven academic systems, which we have also compared against four commercial products. This paper presents our findings.

Book Title
Proc. of the 12th Intl Conf. on Document Analysis and Recognition (ICDAR)
Note
Competition Report.
Pages
1449–1453
Year
2013