Using the watershed transform for iris detection (Contributo in volume (capitolo o saggio))

Type
Label
  • Using the watershed transform for iris detection (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
  • 10.1007/978-3-642-41181-7_28 (literal)
Alternative label
  • Frucci M, Nappi M, Riccio D, Sanniti di Baja G (2013)
    Using the watershed transform for iris detection
    in Image Analysis and Processing - ICIAP 2013, 2013
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Frucci M, Nappi M, Riccio D, Sanniti di Baja G (literal)
Pagina inizio
  • 269 (literal)
Pagina fine
  • 278 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://link.springer.com/chapter/10.1007%2F978-3-642-41184-7_28 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Image Analysis and Processing - ICIAP 2013 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 8157 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 10 (literal)
Note
  • Google Scholar (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Università degli Studi di Salerno Università degli Studi di Napoli Federico II (literal)
Titolo
  • Using the watershed transform for iris detection (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-3-642-41183-0 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autoriVolume
  • Petrosino A. (literal)
Abstract
  • Iris biometric systems are of interest for security applications. In this respect, iris segmentation has a key role, as it must be fast and accurate. In this paper, we present a new watershed based approach for iris segmentation in color images. The watershed transform is used in two distinct phases of iris segmentation: it is first used to obtain a preliminary segmentation, which constitutes the input to a circle fitting procedure; then, it is used together with the portion of the input image resulting after circle fitting to identify more precisely the pixels actually belonging to the iris. The experimental results show that the suggested approach is effective with respect to both location accuracy and computational complexity. (literal)
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