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Automatic segmentation for textured object images

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dc.contributor.authorPark, C.-M.-
dc.contributor.authorKim, C.-G.-
dc.date.accessioned2022-12-26T21:05:02Z-
dc.date.available2022-12-26T21:05:02Z-
dc.date.issued2016-
dc.identifier.issn1975-0080-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/16621-
dc.description.abstractIn this paper, we proposed an automatic segmentation method of object color images with irregular texture. Recently segmentation often used for the image retrieval and in the application. It is more important to approximate the regions than to decide precise region boundary. A color image is divided into blocks, and edge strength for each block is computed by using the modified color histogram intersection method that has been developed to differentiate object boundaries from irregular texture boundaries effectively. The edge strength is defined to have high values at the object boundaries, while it is designed to have relatively low values at the texture boundaries or in the interior of a region. The proposed method works based on small-size blocks, the color histogram of each of which is computed preliminarily once. Thus it works fast but provides rough segmentation. A hybrid color quantization method is used to select a small number of appropriately quantized colors quickly. The proposed method can be applicable for the segmentation in object based image retrieval. ? 2016 SERSC.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherScience and Engineering Research Support Society-
dc.titleAutomatic segmentation for textured object images-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.14257/ijmue.2016.11.9.10-
dc.identifier.scopusid2-s2.0-84989336873-
dc.identifier.bibliographicCitationInternational Journal of Multimedia and Ubiquitous Engineering, v.11, no.9, pp 93 - 100-
dc.citation.titleInternational Journal of Multimedia and Ubiquitous Engineering-
dc.citation.volume11-
dc.citation.number9-
dc.citation.startPage93-
dc.citation.endPage100-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordAuthorEdge-
dc.subject.keywordAuthorHistogram intersection-
dc.subject.keywordAuthorIrregular texture-
dc.subject.keywordAuthorQuantization-
dc.subject.keywordAuthorSegmentation-
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