Source:http://linkedlifedata.com/resource/pubmed/id/18262997
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
9
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| pubmed:dateCreated |
2008-2-11
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| pubmed:abstractText |
In this paper, an algorithm is developed for segmenting document images into four classes: background, photograph, text, and graph. Features used for classification are based on the distribution patterns of wavelet coefficients in high frequency bands. Two important attributes of the algorithm are its multiscale nature-it classifies an image at different resolutions adaptively, enabling accurate classification at class boundaries as well as fast classification overall-and its use of accumulated context information for improving classification accuracy.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:status |
PubMed-not-MEDLINE
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| pubmed:issn |
1057-7149
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| pubmed:author | |
| pubmed:issnType |
Print
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| pubmed:volume |
9
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
1604-16
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| pubmed:year |
2000
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| pubmed:articleTitle |
Context-based multiscale classification of document images using wavelet coefficient distributions.
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| pubmed:affiliation |
Xerox Palo Alto Research Center, Palo Alto, CA 94304, USA. jiali@isl.stanford.edu
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| pubmed:publicationType |
Journal Article
|