Recognizing records from the extracted cells of microfilm tables
Proceedings of the 2002 ACM symposium on Document engineering
Detection of Horizontal Lines in Noisy Run Length Encoded Images: The FAST Method
Selected Papers from the First International Workshop on Graphics Recognition, Methods and Applications
A Tabular Survey of Automated Table Processing
GREC '99 Selected Papers from the Third International Workshop on Graphics Recognition, Recent Advances
A Robust Method for Unknown Forms Analysis
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Robust table-form structure analysis based on box-driven reasoning
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
User-Assisted Archive Document Image Analysis for Digital Library Construction
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Consensus-Based Table Form Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
DIAL '04 Proceedings of the First International Workshop on Document Image Analysis for Libraries (DIAL'04)
Document Image Analysis for World War II Personal Records
DIAL '04 Proceedings of the First International Workshop on Document Image Analysis for Libraries (DIAL'04)
DIAL '04 Proceedings of the First International Workshop on Document Image Analysis for Libraries (DIAL'04)
A survey of table recognition: Models, observations, transformations, and inferences
International Journal on Document Analysis and Recognition
Graphics Recognition. Recent Advances and New Opportunities
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We present a system that recognizes tables in archival documents. Many works were carried out on table recognition but very few on tables of historical documents. These are difficult to analyze because they are often damaged due to their age and conservation. Therefore we have to introduce knowledge to compensate for missing information and noise in these documents. As there is a very important number of documents of a same type, the cost is not significant to introduce this explicit knowledge. We also want to minimalize the cost to adapt the system for a given document type. The precision of the knowledge given by the user is dependent on the quality of the document. The more the document is damaged, the more the specification has to be precise. We will show in this article how an external minimal knowledge can be sufficient for an efficient recognition system for tables in archival documents.