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Robust document image understanding technologies
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Source Conference on Information and Knowledge Management archive
Proceedings of the 1st ACM workshop on Hardcopy document processing table of contents
Washington, DC, USA
Pages: 9 - 14  
Year of Publication: 2004
ISBN:1-58113-976-4
Authors
Henry S. Baird  Lehigh University, Bethlehem, PA
Daniel Lopresti  Lehigh University, Bethlehem, PA
Brian D. Davison  Lehigh University, Bethlehem, PA
William M. Pottenger  Lehigh University, Bethlehem, PA
Sponsors
SIGIR: ACM Special Interest Group on Information Retrieval
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

No existing document image understanding technology, whether experimental or commercially available, can guarantee high accuracy across the full range of documents of interest to industrial and government agency users. Ideally, users should be able to search, access, examine, and navigate among document images as effectively as they can among encoded data files, using familiar interfaces and tools as fully as possible. We are investigating novel algorithms and software tools at the frontiers of document image analysis, information retrieval, text mining, and visualization that will assist in the full integration of such documents into collections of textual document images as well as "born digital" documents. Our approaches emphasize <i>versatility first</i>: that is, methods which work reliably across the broadest possible range of documents.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Henry S. Baird: colleagues
Daniel Lopresti: colleagues
Brian D. Davison: colleagues
William M. Pottenger: colleagues