An a contrario decision method for shape element recognition

Musé, Pablo - Sur, Frederic - Cao, Frederic - Gousseau, Yann

Resumen:

Shape recognition is the field of computer vision which addresses the problem of finding out whethera query shape lies or not in a shape database, up to a certain invariance. Most shape recognition methods simplysort shapes from the database along some (dis-)similarity measure to the query shape. Their main weakness is thedecision stage, which should aim at giving a clear-cut answer to the question: “do these two shapes look alike?”In this article, the proposed solution consists in bounding the number of false correspondences of the query shapeamong the database shapes, ensuring that the obtained matches are not likely to occur “by chance”. As an application,one can decide with a parameterless method whether any two digital images share some shapes or not


Detalles Bibliográficos
2005
Planar shape recognition
Background model
Number of false alarms
Meaningful matches
Level lines
PROCESAMIENTO de SEÑALES
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/21194
Acceso abierto
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author Musé, Pablo
author2 Sur, Frederic
Cao, Frederic
Gousseau, Yann
author2_role author
author
author
author_facet Musé, Pablo
Sur, Frederic
Cao, Frederic
Gousseau, Yann
author_role author
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dc.creator.none.fl_str_mv Musé, Pablo
Sur, Frederic
Cao, Frederic
Gousseau, Yann
dc.date.accessioned.none.fl_str_mv 2019-07-03T16:35:57Z
dc.date.available.none.fl_str_mv 2019-07-03T16:35:57Z
dc.date.issued.es.fl_str_mv 2005
dc.date.submitted.es.fl_str_mv 20190703
dc.description.abstract.none.fl_txt_mv Shape recognition is the field of computer vision which addresses the problem of finding out whethera query shape lies or not in a shape database, up to a certain invariance. Most shape recognition methods simplysort shapes from the database along some (dis-)similarity measure to the query shape. Their main weakness is thedecision stage, which should aim at giving a clear-cut answer to the question: “do these two shapes look alike?”In this article, the proposed solution consists in bounding the number of false correspondences of the query shapeamong the database shapes, ensuring that the obtained matches are not likely to occur “by chance”. As an application,one can decide with a parameterless method whether any two digital images share some shapes or not
dc.identifier.citation.es.fl_str_mv Musé, P., Sur, F., Cao, F., Gousseau, Y. An a contrario decision method for shape element recognition. International Journal of Computer Vision, 2006, v. 69, no.3
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12008/21194
dc.language.iso.none.fl_str_mv en
eng
dc.publisher.es.fl_str_mv Elsevier
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.es.fl_str_mv Planar shape recognition
Background model
Number of false alarms
Meaningful matches
Level lines
dc.subject.other.es.fl_str_mv PROCESAMIENTO de SEÑALES
dc.title.none.fl_str_mv An a contrario decision method for shape element recognition
dc.type.es.fl_str_mv Artículo
dc.type.none.fl_str_mv info:eu-repo/semantics/article
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
description Shape recognition is the field of computer vision which addresses the problem of finding out whethera query shape lies or not in a shape database, up to a certain invariance. Most shape recognition methods simplysort shapes from the database along some (dis-)similarity measure to the query shape. Their main weakness is thedecision stage, which should aim at giving a clear-cut answer to the question: “do these two shapes look alike?”In this article, the proposed solution consists in bounding the number of false correspondences of the query shapeamong the database shapes, ensuring that the obtained matches are not likely to occur “by chance”. As an application,one can decide with a parameterless method whether any two digital images share some shapes or not
eu_rights_str_mv openAccess
format article
id COLIBRI_5f50bc3a429c4bbaf7ca72d9ed15491e
identifier_str_mv Musé, P., Sur, F., Cao, F., Gousseau, Y. An a contrario decision method for shape element recognition. International Journal of Computer Vision, 2006, v. 69, no.3
instacron_str Universidad de la República
institution Universidad de la República
instname_str Universidad de la República
language eng
language_invalid_str_mv en
network_acronym_str COLIBRI
network_name_str COLIBRI
oai_identifier_str oai:colibri.udelar.edu.uy:20.500.12008/21194
publishDate 2005
reponame_str COLIBRI
repository.mail.fl_str_mv mabel.seroubian@seciu.edu.uy
repository.name.fl_str_mv COLIBRI - Universidad de la República
repository_id_str 4771
spelling 2019-07-03T16:35:57Z2019-07-03T16:35:57Z200520190703Musé, P., Sur, F., Cao, F., Gousseau, Y. An a contrario decision method for shape element recognition. International Journal of Computer Vision, 2006, v. 69, no.3https://hdl.handle.net/20.500.12008/21194Shape recognition is the field of computer vision which addresses the problem of finding out whethera query shape lies or not in a shape database, up to a certain invariance. Most shape recognition methods simplysort shapes from the database along some (dis-)similarity measure to the query shape. Their main weakness is thedecision stage, which should aim at giving a clear-cut answer to the question: “do these two shapes look alike?”In this article, the proposed solution consists in bounding the number of false correspondences of the query shapeamong the database shapes, ensuring that the obtained matches are not likely to occur “by chance”. As an application,one can decide with a parameterless method whether any two digital images share some shapes or notMade available in DSpace on 2019-07-03T16:35:57Z (GMT). No. of bitstreams: 4 license_text: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) license_url: 49 bytes, checksum: 4afdbb8c545fd630ea7db775da747b2f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) license.txt: 4267 bytes, checksum: 6429389a7df7277b72b7924fdc7d47a9 (MD5) Previous issue date: 2005enengElsevierLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessPlanar shape recognitionBackground modelNumber of false alarmsMeaningful matchesLevel linesPROCESAMIENTO de SEÑALESAn a contrario decision method for shape element recognitionArtículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaMusé, PabloSur, FredericCao, FredericGousseau, YannProcesamiento de SeñalesTratamiento de 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- Universidad de la Repúblicafalse
spellingShingle An a contrario decision method for shape element recognition
Musé, Pablo
Planar shape recognition
Background model
Number of false alarms
Meaningful matches
Level lines
PROCESAMIENTO de SEÑALES
status_str publishedVersion
title An a contrario decision method for shape element recognition
title_full An a contrario decision method for shape element recognition
title_fullStr An a contrario decision method for shape element recognition
title_full_unstemmed An a contrario decision method for shape element recognition
title_short An a contrario decision method for shape element recognition
title_sort An a contrario decision method for shape element recognition
topic Planar shape recognition
Background model
Number of false alarms
Meaningful matches
Level lines
PROCESAMIENTO de SEÑALES
url https://hdl.handle.net/20.500.12008/21194