Daniel P. Lopresti
“Robust Document Image
Understanding Technologies” (with H. Baird, B. Davison, and W. M.
Pottenger), Proceedings of the First
ACM Workshop
on Hardcopy Document Processing (in association with Thirteenth
Conference on Information and Knowledge Management), November
2004, Washington, DC, pp. 9-14.
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 versatility first:
that is, methods which work reliably across the broadest possible range
of documents.
Paper ( PDF 56 kbytes)
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