Automatic table detection in document images

Authors:
Basilios Gatos;Dimitrios Danatsas;Ioannis Pratikakis;Stavros J. Perantonis
Affiliations:
Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, Athens, Greece;Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, Athens, Greece;Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, Athens, Greece;Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, Athens, Greece
Venue:
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Year:
2005

Citing 7
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Abstract

In this paper, we propose a novel technique for automatic table detection in document images. Lines and tables are among the most frequent graphic, non-textual entities in documents and their detection is directly related to the OCR performance as well as to the document layout description. We propose a workflow for table detection that comprises three distinct steps: (i) image pre-processing; (ii) horizontal and vertical line detection and (iii) table detection. The efficiency of the proposed method is demonstrated by using a performance evaluation scheme which considers a great variety of documents such as forms, newspapers/magazines, scientific journals, tickets/bank cheques, certificates and handwritten documents.