dc.contributorInstituto Federal de Educação, Ciência e Tecnologia de Mato Grosso - IFMT
dc.contributorInstituto Superior Técnico - IST
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:26:11Z
dc.date.accessioned2022-10-05T18:29:55Z
dc.date.available2014-05-27T11:26:11Z
dc.date.available2022-10-05T18:29:55Z
dc.date.created2014-05-27T11:26:11Z
dc.date.issued2011-11-28
dc.identifierLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7042 LNCS, p. 533-540.
dc.identifier0302-9743
dc.identifier1611-3349
dc.identifierhttp://hdl.handle.net/11449/72815
dc.identifier10.1007/978-3-642-25085-9_63
dc.identifier2-s2.0-81855177127
dc.identifier9103545004507135
dc.identifier0000-0002-7069-0479
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3921846
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.
dc.languageeng
dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation0,295
dc.rightsAcesso aberto
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 detection
dc.typeTrabalho apresentado em evento


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