DocumentCode
3490466
Title
ICDAR 2013 Table Competition
Author
Gobel, Max ; Hassan, Thomas ; Oro, Ermelinda ; Orsi, Giorgio
Author_Institution
Tech. Univ. Wien, Vienna, Austria
fYear
2013
fDate
25-28 Aug. 2013
Firstpage
1449
Lastpage
1453
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.
Keywords
document image processing; ICDAR 2013 Table Competition; PDF; academic approach; academic systems; born-digital formats; commercial approach; commercial products; document analysis; document formats; object-based formats; plain text; scanned page images; table location; table recognition; table structure recognition; Educational institutions; Electronic mail; HTML; Measurement; Portable document format; Text analysis; Training; PDF; born-digital PDF; document analysis; document understanding; table location; table recognition; table structure recognition; table understanding;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
Conference_Location
Washington, DC
ISSN
1520-5363
Type
conf
DOI
10.1109/ICDAR.2013.292
Filename
6628853
Link To Document