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.creator | Onchis, Darian M. | es |
dc.date.accessioned | 2020-02-26T09:10:31Z | |
dc.date.available | 2020-02-26T09:10:31Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Real Jurado, P., Molina Abril, H., Díaz del Río, F., Blanco Trejo, S. y Onchis, D. (2019). Enhanced Parallel Generation of Tree Structures for the Recognition of 3D Images. En MCPR 2019: 11th Mexican Conference on Pattern Recognition (292-301), Querétaro, Mexico: Springer. | |
dc.identifier.isbn | 978-3-030-21076-2 | es |
dc.identifier.issn | 0302-9743 | es |
dc.identifier.uri | https://hdl.handle.net/11441/93648 | |
dc.description.abstract | Segmentations of a digital object based on a connectivity
criterion at n-xel or sub-n-xel level are useful tools in image topological
analysis and recognition. Working with cell complex analogous of digital
objects, an example of this kind of segmentation is that obtained from
the combinatorial representation so called Homological Spanning Forest
(HSF, for short) which, informally, classifies the cells of the complex as
belonging to regions containing the maximal number of cells sharing the
same homological (algebraic homology with coefficient in a field) information.
We design here a parallel method for computing a HSF (using
homology with coefficients in Z/2Z) of a 3D digital object. If this object
is included in a 3D image of m1 × m2 × m3 voxels, its theoretical time
complexity order is near O(log(m1 + m2 + m3)), under the assumption
that a processing element is available for each voxel. A prototype implementation
validating our results has been written and several synthetic,
random and medical tridimensional images have been used for testing.
The experiments allow us to assert that the number of iterations in which
the homological information is found varies only to a small extent from
the theoretical computational time. | 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 | MCPR 2019: 11th Mexican Conference on Pattern Recognition (2019), p 292-301 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | 3D digital images | es |
dc.subject | Parallel computing | es |
dc.subject | Abstract cell complex | es |
dc.subject | Homological Spanning Forest | es |
dc.subject | Crack transport | es |
dc.title | Enhanced Parallel Generation of Tree Structures for the Recognition of 3D Images | 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/10.1007/978-3-030-21077-9_27 | es |
dc.identifier.doi | 10.1007/978-3-030-21077-9_27 | es |
idus.format.extent | 10 | es |
dc.publication.initialPage | 292 | es |
dc.publication.endPage | 301 | es |
dc.eventtitle | MCPR 2019: 11th Mexican Conference on Pattern Recognition | es |
dc.eventinstitution | Querétaro, Mexico | es |
dc.relation.publicationplace | Cham, Switzerland | es |