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2002 | OriginalPaper | Buchkapitel

DAN: An Automatic Segmentation and Classification Engine for Paper Documents

verfasst von : L. Cinque, S. Levialdi, A. Malizia, F. De Rosa

Erschienen in: Document Analysis Systems V

Verlag: Springer Berlin Heidelberg

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The paper documents recognition is fundamental for office automation becoming every day a more powerful tool in those fields where information is still on paper. Document recognition follows from data acquisition, from both journals, and entire books in order to transform them in digital objects. We present a new system DAN (Document Analysis on Network) for Document recognition that follows the Open Source methodologies, XML description for documents segmentation and classification, which turns to be beneficial in terms of classification precision, and general-purpose availability.

Metadaten
Titel
DAN: An Automatic Segmentation and Classification Engine for Paper Documents
verfasst von
L. Cinque
S. Levialdi
A. Malizia
F. De Rosa
Copyright-Jahr
2002
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/3-540-45869-7_52

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