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http://acervodigital.unesp.br/handle/11449/72815
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DC Field | Value | Language |
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dc.contributor.author | Statella, Thiago | - |
dc.contributor.author | Pina, Pedro | - |
dc.contributor.author | Silva, Erivaldo Antonio da | - |
dc.date.accessioned | 2014-05-27T11:26:11Z | - |
dc.date.accessioned | 2016-10-25T18:35:40Z | - |
dc.date.available | 2014-05-27T11:26:11Z | - |
dc.date.available | 2016-10-25T18:35:40Z | - |
dc.date.issued | 2011-11-28 | - |
dc.identifier | http://dx.doi.org/10.1007/978-3-642-25085-9_63 | - |
dc.identifier.citation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7042 LNCS, p. 533-540. | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.issn | 1611-3349 | - |
dc.identifier.uri | http://hdl.handle.net/11449/72815 | - |
dc.identifier.uri | http://acervodigital.unesp.br/handle/11449/72815 | - |
dc.description.abstract | This 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.extent | 533-540 | - |
dc.language.iso | eng | - |
dc.source | Scopus | - |
dc.subject | Dust Devils Tracks | - |
dc.subject | Feature Detection | - |
dc.subject | Mars | - |
dc.subject | Mathematical Morphology | - |
dc.subject | Automatic Detection | - |
dc.subject | Automatic method | - |
dc.subject | Data sets | - |
dc.subject | Dust devils | - |
dc.subject | Feature detection | - |
dc.subject | Ground truth | - |
dc.subject | Martian dust | - |
dc.subject | Surface of Mars | - |
dc.subject | Time of processing | - |
dc.subject | Computer vision | - |
dc.subject | Dust | - |
dc.subject | Statistical tests | - |
dc.subject | Surface testing | - |
dc.subject | Mathematical morphology | - |
dc.title | A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection | en |
dc.type | outro | - |
dc.contributor.institution | Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso - IFMT | - |
dc.contributor.institution | Instituto Superior Técnico - IST | - |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | - |
dc.description.affiliation | Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso - IFMT, 95 Zulmira Canavarro, 780025-200, Cuiabá | - |
dc.description.affiliation | Centro de Recursos Naturais e Ambiente Instituto Superior Técnico - IST, Av. Rovisco Pais, 1049-001, Lisboa | - |
dc.description.affiliation | Universidade Estadual Paulista Faculdade de Ciências e Tecnologia - FCT, 305 Roberto Simonsen, 19060-900, Presidente Prudente | - |
dc.description.affiliationUnesp | Universidade Estadual Paulista Faculdade de Ciências e Tecnologia - FCT, 305 Roberto Simonsen, 19060-900, Presidente Prudente | - |
dc.identifier.doi | 10.1007/978-3-642-25085-9_63 | - |
dc.rights.accessRights | Acesso restrito | - |
dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.identifier.scopus | 2-s2.0-81855177127 | - |
Appears in Collections: | Artigos, TCCs, Teses e Dissertações da Unesp |
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