dc.creator | Real Jurado, Pedro | es |
dc.creator | Molina Abril, Helena | es |
dc.creator | Díaz del Río, Fernando | es |
dc.creator | Blanco Trejo, Sergio | es |
dc.date.accessioned | 2020-02-26T10:22:07Z | |
dc.date.available | 2020-02-26T10:22:07Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Real Jurado, P., Molina Abril, H., Díaz del Río, F. y Blanco Trejo, S. (2019). Homological Region Adjacency Tree for a 3D Binary Digital Image via HSF Model. En CAIP 2019: 18th International Conference on Computer Analysis of Images and Patterns (375-387), Salerno, Italy: Springer. | |
dc.identifier.isbn | 978-3-030-29887-6 | es |
dc.identifier.issn | 0302-9743 | es |
dc.identifier.uri | https://hdl.handle.net/11441/93652 | |
dc.description.abstract | Given a 3D binary digital image I, we define and compute
an edge-weighted tree, called Homological Region Tree (or Hom-Tree,
for short). It coincides, as unweighted graph, with the classical Region
Adjacency Tree of black 6-connected components (CCs) and white 26-
connected components of I. In addition, we define the weight of an edge
(R, S) as the number of tunnels that the CCs R and S “share”. The
Hom-Tree structure is still an isotopic invariant of I. Thus, it provides
information about how the different homology groups interact between
them, while preserving the duality of black and white CCs.
An experimentation with a set of synthetic images showing different
shapes and different complexity of connected component nesting is performed
for numerically validating the method. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad MTM2016-81030-P | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | CAIP 2019: 18th International Conference on Computer Analysis of Images and Patterns (2019), p 375-387 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Binary 3D digital image | es |
dc.subject | Region Adjacency Tree | es |
dc.subject | Combinatorial topology | es |
dc.subject | Homological Spanning Forest | es |
dc.title | Homological Region Adjacency Tree for a 3D Binary Digital Image via HSF Model | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería Aeroespacial y Mecánica de Fluidos | es |
dc.relation.projectID | MTM2016-81030-P | es |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-030-29888-3_30 | es |
dc.identifier.doi | 10.1007/978-3-030-29888-3_30 | es |
idus.format.extent | 13 | es |
dc.publication.initialPage | 375 | es |
dc.publication.endPage | 387 | es |
dc.eventtitle | CAIP 2019: 18th International Conference on Computer Analysis of Images and Patterns | es |
dc.eventinstitution | Salerno, Italy | es |
dc.relation.publicationplace | Cham, Switzerland | es |