DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박성하 | ko |
dc.contributor.author | 이창옥 | ko |
dc.contributor.author | 한주영 | ko |
dc.date.accessioned | 2015-04-08T05:16:08Z | - |
dc.date.available | 2015-04-08T05:16:08Z | - |
dc.date.created | 2015-03-19 | - |
dc.date.created | 2015-03-19 | - |
dc.date.created | 2015-03-19 | - |
dc.date.issued | 2014-06 | - |
dc.identifier.citation | Journal of the Korean Society for Industrial and Applied Mathematics, v.18, no.2, pp.129 - 142 | - |
dc.identifier.issn | 1226-9433 | - |
dc.identifier.uri | http://hdl.handle.net/10203/195653 | - |
dc.description.abstract | We propose a variational segmentation model based on statistical information ofintensities in an image. The model consists of both a local region-based energy and a globalregion-based energy in order to handle misclassification which happens in a typical statisticalvariational model with an assumption that an image is a mixture of two Gaussian distributions. We find local ambiguous regions where misclassification might happen due to a small differencebetween two Gaussian distributions. Based on statistical information restricted to the localambiguous regions, we design a local region-based energy in order to reduce the misclassification. We suggest an algorithm to avoid the difficulty of the Euler-Lagrange equations of theproposed variational model. | - |
dc.language | Korean | - |
dc.publisher | 한국산업응용수학회 | - |
dc.title | IMAGE SEGMENTATION BASED ON THE STATISTICAL VARIATIONAL FORMULATION USING THE LOCAL REGION INFORMATION | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.volume | 18 | - |
dc.citation.issue | 2 | - |
dc.citation.beginningpage | 129 | - |
dc.citation.endingpage | 142 | - |
dc.citation.publicationname | Journal of the Korean Society for Industrial and Applied Mathematics | - |
dc.identifier.kciid | ART001885222 | - |
dc.contributor.localauthor | 이창옥 | - |
dc.contributor.nonIdAuthor | 한주영 | - |
dc.subject.keywordAuthor | Image segmentation | - |
dc.subject.keywordAuthor | Statistical variational formulation | - |
dc.subject.keywordAuthor | Region competition | - |
dc.subject.keywordAuthor | Muitidimensional Gaussian PDF | - |
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