eXEDRA: A complete open source architecture for paper document recognition

L. Cinque; S. Levialdi; A. Malizia

doi:10.1109/CAMP.2003.1598152

eXEDRA: A complete open source architecture for paper document recognition

L. Cinque, S. Levialdi, A. Malizia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The Automatic Document 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 architecture for Document recognition that follows the Open Source methodologies for documents segmentation and classification, which turns to be beneficial in terms of computation efficiency, general-purpose availability and cost.

Original language	English
Title of host publication	2003 IEEE International Workshop on Computer Architecture for Machine Perception, CAMP 2003
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	86-94
Number of pages	9
ISBN (Electronic)	0780379705, 9780780379701
DOIs	https://doi.org/10.1109/CAMP.2003.1598152
Publication status	Published - 2003
Event	IEEE International Workshop on Computer Architecture for Machine Perception, CAMP 2003 - New Orleans, United States Duration: 12 May 2003 → 16 May 2003

Conference

Conference	IEEE International Workshop on Computer Architecture for Machine Perception, CAMP 2003
Country/Territory	United States
City	New Orleans
Period	12/05/03 → 16/05/03

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10.1109/CAMP.2003.1598152

Cite this

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title = "eXEDRA: A complete open source architecture for paper document recognition",

abstract = "The Automatic Document 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 architecture for Document recognition that follows the Open Source methodologies for documents segmentation and classification, which turns to be beneficial in terms of computation efficiency, general-purpose availability and cost.",

author = "L. Cinque and S. Levialdi and A. Malizia",

year = "2003",

doi = "10.1109/CAMP.2003.1598152",

language = "English",

pages = "86--94",

booktitle = "2003 IEEE International Workshop on Computer Architecture for Machine Perception, CAMP 2003",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "IEEE International Workshop on Computer Architecture for Machine Perception, CAMP 2003 ; Conference date: 12-05-2003 Through 16-05-2003",

}

Cinque, L, Levialdi, S & Malizia, A 2003, eXEDRA: A complete open source architecture for paper document recognition. in 2003 IEEE International Workshop on Computer Architecture for Machine Perception, CAMP 2003., 1598152, Institute of Electrical and Electronics Engineers (IEEE), pp. 86-94, IEEE International Workshop on Computer Architecture for Machine Perception, CAMP 2003, New Orleans, United States, 12/05/03. https://doi.org/10.1109/CAMP.2003.1598152

eXEDRA: A complete open source architecture for paper document recognition. / Cinque, L.; Levialdi, S.; Malizia, A.
2003 IEEE International Workshop on Computer Architecture for Machine Perception, CAMP 2003. Institute of Electrical and Electronics Engineers (IEEE), 2003. p. 86-94 1598152.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - The Automatic Document 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 architecture for Document recognition that follows the Open Source methodologies for documents segmentation and classification, which turns to be beneficial in terms of computation efficiency, general-purpose availability and cost.

AB - The Automatic Document 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 architecture for Document recognition that follows the Open Source methodologies for documents segmentation and classification, which turns to be beneficial in terms of computation efficiency, general-purpose availability and cost.

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M3 - Conference contribution

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BT - 2003 IEEE International Workshop on Computer Architecture for Machine Perception, CAMP 2003

PB - Institute of Electrical and Electronics Engineers (IEEE)

Y2 - 12 May 2003 through 16 May 2003

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eXEDRA: A complete open source architecture for paper document recognition

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