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Client-Driven Content Extraction Associated with Table

Santosh K.C. 1 Abdel Belaïd 1 
1 READ - Recognition of writing and analysis of documents
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : The goal of the project is to extract content within table in document images based on learnt patterns. Real-world users i.e., clients first provide a set of key fields within the table which they think are important. These are first used to represent the graph where nodes are labelled with semantics including other features and edges are attributed with relations. Attributed relational graph (ARG) is then employed to mine similar graphs from a document image. Each mined graph will represent an item within the table, and hence a set of such graphs will compose a table. We have validated the concept by using a real-world industrial problem.
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Submitted on : Friday, April 5, 2013 - 8:32:17 PM
Last modification on : Saturday, October 16, 2021 - 11:26:09 AM
Long-term archiving on: : Monday, April 3, 2017 - 1:13:33 AM


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  • HAL Id : hal-00808678, version 1
  • ARXIV : 1304.1930



Santosh K.C., Abdel Belaïd. Client-Driven Content Extraction Associated with Table. IAPR MVA - The Thirteenth IAPR International Conference on Machine Vision Applications - 2013, May 2013, Kyoto, Japan. ⟨hal-00808678⟩



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