Paper
24 March 2014 LearnPos: a new tool for interactive learning positioning
Author Affiliations +
Proceedings Volume 9021, Document Recognition and Retrieval XXI; 90210H (2014) https://doi.org/10.1117/12.2042379
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
Abstract
The analysis of 2D structured documents often requires localizing data inside of a document during the recognition process. In this paper we present LearnPos a new generic tool, independent of any document recognition system. LearnPos models and evaluates positioning from a learning set of documents. Thanks to LearnPos, the user is helped to define the physical structure of the document. He then can concentrate his efforts on the definition of the logical structure of the documents. LearnPos is able to furnish spatial information for both absolute and relative spatial relations, in interaction with the user. Our method can handle spatial relations compose of distinct zones and is able to furnish appropriate order and point of view to minimize errors. We prove that resulting models can be successfully used for structured document recognition, while reducing the manual exploration of the data set of documents.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Cérès Carton, Aurélie Lemaitre, and Bertrand Coüasnon "LearnPos: a new tool for interactive learning positioning", Proc. SPIE 9021, Document Recognition and Retrieval XXI, 90210H (24 March 2014); https://doi.org/10.1117/12.2042379
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Neodymium

Data modeling

Databases

Fuzzy logic

Error analysis

Image analysis

Image segmentation

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