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Author
Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Benedi
Title
Structure Detection and Segmentation of Documents Using 2D Stochastic Context-Free Grammars
Type
Journal Article
Year
2015
Publication
Neurocomputing
Abbreviated Journal
NEUCOM
Volume
150
Issue
A
Pages
147-154
Keywords
document image analysis; stochastic context-free grammars; text classication features
Abstract
In this paper we dene a bidimensional extension of Stochastic Context-Free Grammars for structure detection and segmentation of images of documents.
Two sets of text classication features are used to perform an initial classication of each zone of the page. Then, the document segmentation is obtained as the most likely hypothesis according to a stochastic grammar. We used a dataset of historical marriage license books to validate this approach. We also tested several inference algorithms for Probabilistic Graphical Models
and the results showed that the proposed grammatical model outperformed
the other methods. Furthermore, grammars also provide the document structure
along with its segmentation.
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DAG; 601.158; 600.077; 600.061
Approved
no
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Admin @ si @ ACS2015
Serial
2531
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