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. © Springer-Verlag Berlin Heidelberg 2002.
DAN: An automatic segmentation and classification engine for paper documents
Malizia A;
2002-01-01
Abstract
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. © Springer-Verlag Berlin Heidelberg 2002.File in questo prodotto:
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