Fast neighborhood operations for images and volume datasets

This paper presents a new approach to carry out erosion, dilation and connected component labeling. We use the Extreme Vertices Model (EVM), an orthogonal polyhedra representation, to describe binary images and volume datasets in a very efficient way. Our proposal does not use a voxel-based approach...

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Detalhes bibliográficos
Autores: Rodríguez Rojas, Jorge Ernesto, Ayala Vallespí, M. Dolors|||0000-0003-4931-0467
Tipo de documento: relatório científico
Data de publicação:2003
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositório:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglês
OAI Identifier:oai:upcommons.upc.edu:2117/97390
Acesso em linha:https://hdl.handle.net/2117/97390
Access Level:Acceso aberto
Palavra-chave:Extreme Vertices Model
EVM
Fast neighborhood operations
Images and volumes datasets
Morfological operations
Connected component labeling
Non-manifold zones
Àrees temàtiques de la UPC::Informàtica
Descrição
Resumo:This paper presents a new approach to carry out erosion, dilation and connected component labeling. We use the Extreme Vertices Model (EVM), an orthogonal polyhedra representation, to describe binary images and volume datasets in a very efficient way. Our proposal does not use a voxel-based approach but deals with the inner sections of the object. It allows to treat images and volumes indistinctly using the same algorithm and data structure with no overhead of memory and can be applied to manifold as well as non-manifold data. The connected component labeling algorithm actually detects non-manifold zones and permits to break or not the objects at these zones by an user-specified parameter.