Cell AT-models for digital volumes

In [4], given a binary 26-adjacency voxel-based digital volume V, the homological information (that related to n-dimensional holes: connected components, ”tunnels” and cavities) is extracted from a linear map (called homology gradient vector field) acting on a polyhedral cell complex P(V) homologica...

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Detalhes bibliográficos
Autores: Real Jurado, Pedro, Molina Abril, Helena
Tipo de documento: capítulo de livro
Estado:Versión enviada para evaluación y publicación
Data de publicação:2009
País:España
Recursos:Universidad de Sevilla (US)
Repositório:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/31749
Acesso em linha:http://hdl.handle.net/11441/31749
https://doi.org/10.1007/978-3-642-02124-4_32
Access Level:Acceso aberto
Palavra-chave:Pattern Recognition
Image Processing and Computer Vision
Computer Imaging
Vision
Pattern Recognition and Graphics
Computer Graphics
Discrete Mathematics in Computer Science
Artificial Intelligence (incl. Robotics)
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spelling Cell AT-models for digital volumesReal Jurado, PedroMolina Abril, HelenaPattern RecognitionImage Processing and Computer VisionComputer ImagingVisionPattern Recognition and GraphicsComputer GraphicsDiscrete Mathematics in Computer ScienceArtificial Intelligence (incl. Robotics)In [4], given a binary 26-adjacency voxel-based digital volume V, the homological information (that related to n-dimensional holes: connected components, ”tunnels” and cavities) is extracted from a linear map (called homology gradient vector field) acting on a polyhedral cell complex P(V) homologically equivalent to V. We develop here an alternative way for constructing P(V) based on homological algebra arguments as well as a new more efficient algorithm for computing a homology gradient vector field based on the contractibility of the maximal cells of P(V).Matemática Aplicada I2009info:eu-repo/semantics/bookPartinfo:eu-repo/semantics/submittedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/11441/31749https://doi.org/10.1007/978-3-642-02124-4_32reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésGraph-Based Representations in Pattern Recognition, Lecture Notes in Computer Science, Vol. 5534 p. 314-323info:eu-repo/semantics/openAccessoai:idus.us.es:11441/317492026-06-17T12:51:07Z
dc.title.none.fl_str_mv Cell AT-models for digital volumes
title Cell AT-models for digital volumes
spellingShingle Cell AT-models for digital volumes
Real Jurado, Pedro
Pattern Recognition
Image Processing and Computer Vision
Computer Imaging
Vision
Pattern Recognition and Graphics
Computer Graphics
Discrete Mathematics in Computer Science
Artificial Intelligence (incl. Robotics)
title_short Cell AT-models for digital volumes
title_full Cell AT-models for digital volumes
title_fullStr Cell AT-models for digital volumes
title_full_unstemmed Cell AT-models for digital volumes
title_sort Cell AT-models for digital volumes
dc.creator.none.fl_str_mv Real Jurado, Pedro
Molina Abril, Helena
author Real Jurado, Pedro
author_facet Real Jurado, Pedro
Molina Abril, Helena
author_role author
author2 Molina Abril, Helena
author2_role author
dc.contributor.none.fl_str_mv Matemática Aplicada I
dc.subject.none.fl_str_mv Pattern Recognition
Image Processing and Computer Vision
Computer Imaging
Vision
Pattern Recognition and Graphics
Computer Graphics
Discrete Mathematics in Computer Science
Artificial Intelligence (incl. Robotics)
topic Pattern Recognition
Image Processing and Computer Vision
Computer Imaging
Vision
Pattern Recognition and Graphics
Computer Graphics
Discrete Mathematics in Computer Science
Artificial Intelligence (incl. Robotics)
description In [4], given a binary 26-adjacency voxel-based digital volume V, the homological information (that related to n-dimensional holes: connected components, ”tunnels” and cavities) is extracted from a linear map (called homology gradient vector field) acting on a polyhedral cell complex P(V) homologically equivalent to V. We develop here an alternative way for constructing P(V) based on homological algebra arguments as well as a new more efficient algorithm for computing a homology gradient vector field based on the contractibility of the maximal cells of P(V).
publishDate 2009
dc.date.none.fl_str_mv 2009
dc.type.none.fl_str_mv info:eu-repo/semantics/bookPart
info:eu-repo/semantics/submittedVersion
format bookPart
status_str submittedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11441/31749
https://doi.org/10.1007/978-3-642-02124-4_32
url http://hdl.handle.net/11441/31749
https://doi.org/10.1007/978-3-642-02124-4_32
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Graph-Based Representations in Pattern Recognition, Lecture Notes in Computer Science, Vol. 5534 p. 314-323
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301629

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