Word Spotting in Bitmapped Fax Documents
dc.contributor.author | Williams, William J. | en_US |
dc.contributor.author | Zalubas, Eugene J. | en_US |
dc.contributor.author | Hero, Alfred O. III | en_US |
dc.date.accessioned | 2006-09-11T17:14:40Z | |
dc.date.available | 2006-09-11T17:14:40Z | |
dc.date.issued | 2000-05 | en_US |
dc.identifier.citation | Williams, William J.; Zalubas, Eugene J.; Hero, Alfred O.; (2000). "Word Spotting in Bitmapped Fax Documents." Information Retrieval 2 (2-3): 207-226. <http://hdl.handle.net/2027.42/45988> | en_US |
dc.identifier.issn | 1386-4564 | en_US |
dc.identifier.issn | 1573-7659 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/45988 | |
dc.description.abstract | Images and signals may be represented by forms invariant to time shifts, spatial shifts, frequency shifts, and scale changes. Advances in time-frequency analysis and scale transform techniques have made this possible. However, factors such as noise contamination and “style” differences complicate this. An example is found in text, where letters and words may vary in size and position. Examples of complicating variations include the font used, corruption during facsimile (fax) transmission, and printer characteristics. The solution advanced in this paper is to cast the desired invariants into separate subspaces for each extraneous factor or group of factors. The first goal is to have minimal overlap between these subspaces and the second goal is to be able to identify each subspace accurately. Concepts borrowed from high-resolution spectral analysis, but adapted uniquely to this problem have been found to be useful in this context. Once the pertinent subspace is identified, the recognition of a particular invariant form within this subspace is relatively simple using well-known singular value decomposition (SVD) techniques. The basic elements of the approach can be applied to a variety of pattern recognition problems. The specific application covered in this paper is word spotting in bitmapped fax documents. | en_US |
dc.format.extent | 273597 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Computer Science | en_US |
dc.subject.other | Data Structures, Cryptology and Information Theory | en_US |
dc.subject.other | Management of Computing and Information Systems | en_US |
dc.subject.other | Word Spotting | en_US |
dc.subject.other | Facsimile | en_US |
dc.subject.other | Scale | en_US |
dc.subject.other | Position | en_US |
dc.subject.other | Invariant | en_US |
dc.title | Word Spotting in Bitmapped Fax Documents | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Philosophy | en_US |
dc.subject.hlbsecondlevel | Computer Science | en_US |
dc.subject.hlbtoplevel | Humanities | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Electrical Engineering and Computer Science Dept., University of Michigan, Ann Arbor, MI, 48109, USA | en_US |
dc.contributor.affiliationum | Electrical Engineering and Computer Science Dept., University of Michigan, Ann Arbor, MI, 48109, USA | en_US |
dc.contributor.affiliationum | Electrical Engineering and Computer Science Dept., University of Michigan, Ann Arbor, MI, 48109, USA | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/45988/1/10791_2004_Article_260693.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/A:1009958827317 | en_US |
dc.identifier.source | Information Retrieval | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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