A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection
Autor(a) principal: | |
---|---|
Data de Publicação: | 2011 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/978-3-642-25085-9_63 http://hdl.handle.net/11449/72815 |
Resumo: | 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. |
id |
UNSP_4807d8c78e9f50d8a071a190366a8d01 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/72815 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
A study on automatic methods based on mathematical morphology for Martian dust devil tracks detectionDust Devils TracksFeature DetectionMarsMathematical MorphologyAutomatic DetectionAutomatic methodData setsDust devilsFeature detectionGround truthMartian dustSurface of MarsTime of processingComputer visionDustStatistical testsSurface testingMathematical morphologyThis 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.Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso - IFMT, 95 Zulmira Canavarro, 780025-200, CuiabáCentro de Recursos Naturais e Ambiente Instituto Superior Técnico - IST, Av. Rovisco Pais, 1049-001, LisboaUniversidade Estadual Paulista Faculdade de Ciências e Tecnologia - FCT, 305 Roberto Simonsen, 19060-900, Presidente PrudenteUniversidade Estadual Paulista Faculdade de Ciências e Tecnologia - FCT, 305 Roberto Simonsen, 19060-900, Presidente PrudenteInstituto Federal de Educação, Ciência e Tecnologia de Mato Grosso - IFMTInstituto Superior Técnico - ISTUniversidade Estadual Paulista (Unesp)Statella, ThiagoPina, PedroSilva, Erivaldo Antonio da [UNESP]2014-05-27T11:26:11Z2014-05-27T11:26:11Z2011-11-28info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject533-540http://dx.doi.org/10.1007/978-3-642-25085-9_63Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7042 LNCS, p. 533-540.0302-97431611-3349http://hdl.handle.net/11449/7281510.1007/978-3-642-25085-9_632-s2.0-8185517712791035450045071350000-0002-7069-0479Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)0,295info:eu-repo/semantics/openAccess2021-10-23T21:41:37Zoai:repositorio.unesp.br:11449/72815Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T21:41:37Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection |
title |
A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection |
spellingShingle |
A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection Statella, Thiago Dust Devils Tracks Feature Detection Mars Mathematical Morphology Automatic Detection Automatic method Data sets Dust devils Feature detection Ground truth Martian dust Surface of Mars Time of processing Computer vision Dust Statistical tests Surface testing Mathematical morphology |
title_short |
A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection |
title_full |
A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection |
title_fullStr |
A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection |
title_full_unstemmed |
A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection |
title_sort |
A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection |
author |
Statella, Thiago |
author_facet |
Statella, Thiago Pina, Pedro Silva, Erivaldo Antonio da [UNESP] |
author_role |
author |
author2 |
Pina, Pedro Silva, Erivaldo Antonio da [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso - IFMT Instituto Superior Técnico - IST Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Statella, Thiago Pina, Pedro Silva, Erivaldo Antonio da [UNESP] |
dc.subject.por.fl_str_mv |
Dust Devils Tracks Feature Detection Mars Mathematical Morphology Automatic Detection Automatic method Data sets Dust devils Feature detection Ground truth Martian dust Surface of Mars Time of processing Computer vision Dust Statistical tests Surface testing Mathematical morphology |
topic |
Dust Devils Tracks Feature Detection Mars Mathematical Morphology Automatic Detection Automatic method Data sets Dust devils Feature detection Ground truth Martian dust Surface of Mars Time of processing Computer vision Dust Statistical tests Surface testing Mathematical morphology |
description |
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. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-11-28 2014-05-27T11:26:11Z 2014-05-27T11:26:11Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1007/978-3-642-25085-9_63 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7042 LNCS, p. 533-540. 0302-9743 1611-3349 http://hdl.handle.net/11449/72815 10.1007/978-3-642-25085-9_63 2-s2.0-81855177127 9103545004507135 0000-0002-7069-0479 |
url |
http://dx.doi.org/10.1007/978-3-642-25085-9_63 http://hdl.handle.net/11449/72815 |
identifier_str_mv |
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7042 LNCS, p. 533-540. 0302-9743 1611-3349 10.1007/978-3-642-25085-9_63 2-s2.0-81855177127 9103545004507135 0000-0002-7069-0479 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 0,295 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
533-540 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1799964721813651456 |