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dc.contributor.author
Mailing, Agustin Beltran
dc.contributor.author
Crivelli, Tomás
dc.contributor.author
Cernuschi Frias, Bruno
dc.date.available
2023-01-16T10:29:07Z
dc.date.issued
2010
dc.identifier.citation
Model distribution dependant complexity estimation on textures; 6th International Symposium on Visual Computing; Las Vegas; Estados Unidos; 2010; 371-279
dc.identifier.isbn
978-3-642-17276-2
dc.identifier.uri
http://hdl.handle.net/11336/184772
dc.description.abstract
On this work a method for the complexity of a textured image to be estimated is presented. The method allow to detect changes on its stationarity by means of the complexity with respect to a given model set (distribution dependant). That detection is done in such a way that also allows to classify textured images according to the whole texture complexity. When different models are used to model data, the more complex model is expected to fit it better because of the higher degree of freedom. Thus, a naturally-arisen penalization on the model complexity is used in a Bayesian context. Here a nested models scheme is used to improve the robustness and efficiency on the implementation. Even when MRF models are used for the sake of clarity, the procedure it is not subject to a particular distribution.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Springer Verlag Berlín
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
COMPLEXITY
dc.subject
TEXTURED IMAGES
dc.subject
CLASSIFICATION
dc.subject.classification
Ingeniería de Sistemas y Comunicaciones
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Model distribution dependant complexity estimation on textures
dc.type
info:eu-repo/semantics/publishedVersion
dc.type
info:eu-repo/semantics/conferenceObject
dc.type
info:ar-repo/semantics/documento de conferencia
dc.date.updated
2022-11-09T19:35:38Z
dc.journal.volume
6455
dc.journal.number
3
dc.journal.pagination
371-279
dc.journal.pais
Alemania
dc.journal.ciudad
Heildeberg
dc.description.fil
Fil: Mailing, Agustin Beltran. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Electronica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderón; Argentina
dc.description.fil
Fil: Crivelli, Tomás. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Electronica; Argentina
dc.description.fil
Fil: Cernuschi Frias, Bruno. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderón; Argentina
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/978-3-642-17277-9_28
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/chapter/10.1007/978-3-642-17277-9_28
dc.conicet.rol
Autor
dc.conicet.rol
Autor
dc.conicet.rol
Autor
dc.coverage
Internacional
dc.type.subtype
Simposio
dc.description.nombreEvento
6th International Symposium on Visual Computing
dc.date.evento
2010-11-29
dc.description.ciudadEvento
Las Vegas
dc.description.paisEvento
Estados Unidos
dc.type.publicacion
Book
dc.description.institucionOrganizadora
University of Nevada
dc.source.libro
Advances in Visual Computing
dc.date.eventoHasta
2010-12-01
dc.type
Simposio
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