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Hybrid framework to image segmentation

dc.contributor.authorMonteiro, Fernando C.
dc.date.accessioned2010-03-15T11:43:00Z
dc.date.available2010-03-15T11:43:00Z
dc.date.issued2009
dc.descriptionIndexado ISIpt
dc.description.abstractThis paper proposes a new hybrid framework to image segmentation which combines edge- and region-based information with spectral techniques through the morphological algorithm of watersheds. The image is represented by a weighted undirected graph, whose nodes correspond to over-segmented regions (atomic regions), instead of pixels, that decreases the complexity of the overall algorithm. In addition, the link weights between the nodes are calculated through the intensity similarities combined with the intervening contours information among atomic regions. We outline a procedure for algorithm evaluation through the comparison with some of the most popular segmentation algorithms: the mean-shift-based algorithm, a multiscale graph based segmentation method, and JSEG method for multiscale segmentation of colour and texture. Experiments on the Berkeley segmentation database indicate that the proposed segmentation framework yields better segmentation results due to its region-based representation.pt
dc.identifier.citationMonteiro, Fernando C. (2009). Hybrid Framework to Image Segmentation. IN Neural Information Processing. Berlin: Springer-Verlag. ISBN 978-3-642-10682-8. p.657-666.pt
dc.identifier.isbn978-3-642-10682-8
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10198/2241
dc.language.isoengpt
dc.publisherSpringerpt
dc.relation.ispartofseriesLectures Notes in Computer Science;5864
dc.subjectImage segmentationpt
dc.subjectHybrid frameworkpt
dc.subjectWatershedpt
dc.subjectSpectral methodspt
dc.titleHybrid framework to image segmentationpt
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage666pt
oaire.citation.startPage657pt
oaire.citation.titleNeural Information Processingpt
person.familyNameMonteiro
person.givenNameFernando C.
person.identifier.ciencia-id2019-BDBF-10E2
person.identifier.orcid0000-0002-1421-8006
person.identifier.ridH-9213-2016
person.identifier.scopus-author-id8986162600
rcaap.rightsopenAccesspt
rcaap.typebookPartpt
relation.isAuthorOfPublication363b6c37-282c-4cd6-bb54-3c97cc700d78
relation.isAuthorOfPublication.latestForDiscovery363b6c37-282c-4cd6-bb54-3c97cc700d78

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