Image segmentation via histogram thresholding and morphological features analysis (Contributo in volume (capitolo o saggio))

Type
Label
  • Image segmentation via histogram thresholding and morphological features analysis (Contributo in volume (capitolo o saggio)) (literal)
Anno
  • 2008-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1007/978-3-540-69812-8_13 (literal)
Alternative label
  • Brancati N; Frucci M; Sanniti di Baja G (2008)
    Image segmentation via histogram thresholding and morphological features analysis
    in IMAGE ANALYSIS AND RECOGNITION, 2008
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Brancati N; Frucci M; Sanniti di Baja G (literal)
Pagina inizio
  • 132 (literal)
Pagina fine
  • 141 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.springerlink.com/content/yq5538167536u4q1/ (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • IMAGE ANALYSIS AND RECOGNITION (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 5112 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • ICIAR 2008: Lecture Notes in Computer Science, Springer Publ. Vol. 5112, Campilho A., Kamel M. Eds., p. 132–141 (2008) (literal)
Note
  • Scopus (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Istituto di Cibernetica \"E. CAianiello\" (literal)
Titolo
  • Image segmentation via histogram thresholding and morphological features analysis (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-3-540-69811-1 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autoriVolume
  • Campilho A; Kamel M (literal)
Abstract
  • In this paper, we present a new segmentation algorithm, based on iterated thresholding and on morphological features. A first thresholding, based on the histogram of the image, is done to partition the image into three sets including respectively pixels belonging to foreground, pixels belonging to background, and unassigned pixels. Thresholding of components of unassigned pixels is then iteratively done, based on the histogram of the components. Components of unassigned pixels, possibly still present at the end of iterated thresholding, are assigned to foreground or background by taking into account area, minimum grey-level and spatial relationship with the adjacent sets. (literal)
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