http://www.cnr.it/ontology/cnr/individuo/prodotto/ID18726
Using resolution pyramids for watershed image segmentation (Articolo in rivista)
- Type
- Label
- Using resolution pyramids for watershed image segmentation (Articolo in rivista) (literal)
- Anno
- 2007-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.imavis.2006.07.014 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Frucci M; Ramella G; Sanniti di Baja G (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.sciencedirect.com/science/article/pii/S0262885606002241 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto
- Si introduce un metodo per ridurre la oversegmentation in partizioni di immagini a livelli di grigio ottenute mediante watershed transformation, utilizzando strutture a multiscala (literal)
- Note
- Scopu (literal)
- Google Scholar (literal)
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Istituto di Cibernetica \"E.Caianiello\", CNR (literal)
- Titolo
- Using resolution pyramids for watershed image segmentation (literal)
- Abstract
- In this paper we build a shape preserving resolution pyramid and use it in the framework of image segmentation via watershed transformation. Our method is based on the assumption that the most significant image components perceived at high resolution will also be perceived at lower resolution. Thus, we detect the seeds for the watershed transformation at a low resolution, and use them to distinguish significant and non-significant seeds at any selected higher resolution. In this way, the watershed partition obtained at the selected pyramid level will include only the most significant components, and over-segmentation will be considerably reduced. Segmentations of the image at different scales will be available. Moreover, since the seeds can be detected at different pyramid levels, alternative segmentations of the image at a given resolution can be obtained, each characterized by a different level of detail. (literal)
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