Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/30268
COMPARTIR / EXPORTAR:
logo share SHARE BASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE

Invitar a revisión por pares abierta
Título

Fast skeletonization of spatially encoded objects

AutorRomero, Francisco; Ros, Lluís CSIC ORCID ; Thomas, Federico CSIC ORCID
Palabras clavePattern recognition: Computer vision
Computer vision
Fecha de publicación2000
EditorInstitute of Electrical and Electronics Engineers
Citación15th International Conference on Pattern Recognition: 510-513 (2000)
ResumenSome thinning algorithms for 3D objects, or generalizations of existing ones for 2D, have been proposed in recent years. The paper presents a simple and very fast algorithm compared to most of them, and still it has theoretically favorable properties. It provides a connected surface skeleton that allows shapes to be reconstructed with bounded error. In addition, it is also very attractive because it allows discrete skeletons to be obtained directly from volumes in many representations without converting them to a voxel-based representation. Our algorithm is a generalization of the one presented by Cardoner et al. (1997) for 2D objects. It is based on the application of directional erosions, while retaining those voxels that introduce disconnection.
DescripciónInternational Conference on Pattern Recognition (ICPR), Barcelona (España)
URIhttp://hdl.handle.net/10261/30268
DOI10.1109/ICPR.2000.903595
ISBN0769507506
Aparece en las colecciones: (IRII) Comunicaciones congresos




Ficheros en este ítem:
Fichero Descripción Tamaño Formato
doc1.pdf392,89 kBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo

CORE Recommender

Page view(s)

308
checked on 22-abr-2024

Download(s)

208
checked on 22-abr-2024

Google ScholarTM

Check

Altmetric

Altmetric


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.