http://www.cnr.it/ontology/cnr/individuo/prodotto/ID229527
Image segmentation based on representative colors detection and region merging (Contributo in volume (capitolo o saggio))
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- Label
- Image segmentation based on representative colors detection and region merging (Contributo in volume (capitolo o saggio)) (literal)
- Anno
- 2013-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1007/978-3-642-38989-4_18 (literal)
- Alternative label
Ramella G., Sanniti di Baja G. (2013)
Image segmentation based on representative colors detection and region merging
Springer, Berlin Heidelberg (Germania) in Pattern Recognition, 2013
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Ramella G., Sanniti di Baja G. (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
- MCPR 13 - 5th Mexican Conference on Pattern Recognition (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://link.springer.com/chapter/10.1007%2F978-3-642-38989-4_18 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- Pattern Recognition (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
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- The Collection of Computer Science Bibliography (literal)
- SpringerLink (literal)
- Google Scholar (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Istituto di Cibernetica \"E. Caianiello\", CNR (literal)
- Titolo
- Image segmentation based on representative colors detection and region merging (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-3-642-38988-7 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
- Carrasco-Ochoa J. A. et al. (literal)
- Abstract
- We present a color image segmentation algorithm, RCRM, based on the detection of Representative Colors and on Region Merging. The 3D color histogram of the RGB input image is built. Colors are processed in decreasing frequency order and a grouping process is accomplished to gather in the same cluster all colors that are close enough to the current color. Colormapping is done to originate a preliminary image segmentation. Segmentation regions having small size undergo a merging process. Merging is actually accomplished only for adjacent regions whose colors do not significantly differ. The parameters involved by the algorithm are set automatically by taking into account color distribution in the input image and geometrical features of the regions into which the image is partitioned. The algorithm has been tested on a large number of RGB color images originating satisfactory results. (literal)
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