An integration scheme for image segmentation and labeling based on Markov random field model
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim II, Y. | ko |
| dc.contributor.author | Yang, Hyun-Seung | ko |
| dc.date.accessioned | 2007-05-25T02:35:43Z | - |
| dc.date.available | 2007-05-25T02:35:43Z | - |
| dc.date.created | 2012-02-06 | - |
| dc.date.created | 2012-02-06 | - |
| dc.date.issued | 1996 | - |
| dc.identifier.citation | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, v.18, no.1, pp.69 - 73 | - |
| dc.identifier.issn | 0162-8828 | - |
| dc.identifier.uri | http://hdl.handle.net/10203/339 | - |
| dc.description.abstract | This paper presents a unified approach for the image understanding problem based on the MRF models. In the proposed scheme, the image segmentation and interpretation processes cooperate in the simultaneous optimization process so that the erroneous segmentation and misinterpretation can be compensately recovered by continuous estimation of the unified energy function. | - |
| dc.language | English | - |
| dc.language.iso | en_US | en |
| dc.publisher | IEEE COMPUTER SOC | - |
| dc.title | An integration scheme for image segmentation and labeling based on Markov random field model | - |
| dc.type | Article | - |
| dc.identifier.wosid | A1996TP31500009 | - |
| dc.type.rims | ART | - |
| dc.citation.volume | 18 | - |
| dc.citation.issue | 1 | - |
| dc.citation.beginningpage | 69 | - |
| dc.citation.endingpage | 73 | - |
| dc.citation.publicationname | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | - |
| dc.identifier.doi | 10.1109/34.476014 | - |
| dc.embargo.liftdate | 9999-12-31 | - |
| dc.embargo.terms | 9999-12-31 | - |
| dc.contributor.localauthor | Yang, Hyun-Seung | - |
| dc.contributor.nonIdAuthor | Kim II, Y. | - |
| dc.type.journalArticle | Article | - |
| dc.subject.keywordAuthor | region clustering | - |
| dc.subject.keywordAuthor | region labeling | - |
| dc.subject.keywordAuthor | Markov random field | - |
| dc.subject.keywordAuthor | energy function | - |
| dc.subject.keywordAuthor | optimization | - |
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