You are in the accessibility menu

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72815
Full metadata record
DC FieldValueLanguage
dc.contributor.authorStatella, Thiago-
dc.contributor.authorPina, Pedro-
dc.contributor.authorSilva, Erivaldo Antonio da-
dc.date.accessioned2014-05-27T11:26:11Z-
dc.date.accessioned2016-10-25T18:35:40Z-
dc.date.available2014-05-27T11:26:11Z-
dc.date.available2016-10-25T18:35:40Z-
dc.date.issued2011-11-28-
dc.identifierhttp://dx.doi.org/10.1007/978-3-642-25085-9_63-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7042 LNCS, p. 533-540.-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttp://hdl.handle.net/11449/72815-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/72815-
dc.description.abstractThis paper presents three methods for automatic detection of dust devils tracks in images of Mars. The methods are mainly based on Mathematical Morphology and results of their performance are analyzed and compared. A dataset of 21 images from the surface of Mars representative of the diversity of those track features were considered for developing, testing and evaluating our methods, confronting their outputs with ground truth images made manually. Methods 1 and 3, based on closing top-hat and path closing top-hat, respectively, showed similar mean accuracies around 90% but the time of processing was much greater for method 1 than for method 3. Method 2, based on radial closing, was the fastest but showed worse mean accuracy. Thus, this was the tiebreak factor. © 2011 Springer-Verlag.en
dc.format.extent533-540-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectDust Devils Tracks-
dc.subjectFeature Detection-
dc.subjectMars-
dc.subjectMathematical Morphology-
dc.subjectAutomatic Detection-
dc.subjectAutomatic method-
dc.subjectData sets-
dc.subjectDust devils-
dc.subjectFeature detection-
dc.subjectGround truth-
dc.subjectMartian dust-
dc.subjectSurface of Mars-
dc.subjectTime of processing-
dc.subjectComputer vision-
dc.subjectDust-
dc.subjectStatistical tests-
dc.subjectSurface testing-
dc.subjectMathematical morphology-
dc.titleA study on automatic methods based on mathematical morphology for Martian dust devil tracks detectionen
dc.typeoutro-
dc.contributor.institutionInstituto Federal de Educação, Ciência e Tecnologia de Mato Grosso - IFMT-
dc.contributor.institutionInstituto Superior Técnico - IST-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationInstituto Federal de Educação, Ciência e Tecnologia de Mato Grosso - IFMT, 95 Zulmira Canavarro, 780025-200, Cuiabá-
dc.description.affiliationCentro de Recursos Naturais e Ambiente Instituto Superior Técnico - IST, Av. Rovisco Pais, 1049-001, Lisboa-
dc.description.affiliationUniversidade Estadual Paulista Faculdade de Ciências e Tecnologia - FCT, 305 Roberto Simonsen, 19060-900, Presidente Prudente-
dc.description.affiliationUnespUniversidade Estadual Paulista Faculdade de Ciências e Tecnologia - FCT, 305 Roberto Simonsen, 19060-900, Presidente Prudente-
dc.identifier.doi10.1007/978-3-642-25085-9_63-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.identifier.scopus2-s2.0-81855177127-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

There are no files associated with this item.
 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.