Improved automatic impact crater detection on Mars based on morphological image processing and template matching

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dc.contributor.authorPedrosa, Miriam Maria [UNESP]
dc.contributor.authorAzevedo, Samara Calcado de [UNESP]
dc.contributor.authorSilva, Erivaldo Antonio da [UNESP]
dc.contributor.authorDias, Mauricio Araujo [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-11-26T17:44:32Z
dc.date.available2018-11-26T17:44:32Z
dc.date.issued2017-01-01
dc.description.abstractImpact craters help scientists to understand the geological history of planetary bodies. The aim of this paper is to improve the existing methodology for impact craters detection in images of planetary surfaces using a new approach based on morphological image processing (MIP). The improved methodology uses MIP followed by template matching based on fast Fourier transform (FFT). In this phase, a probability volume is generated based on the correlation between templates and images. The analysis of this probability volume allows the detection of different size of impact craters. We have applied the improved methodology to detect impact craters in a set of images from Thermal Emission Imaging System onboard the 2001 Mars Odyssey Space probe. The improved methodology has achieved a crater detection rate of 92.23% which can be considered robust, since results were obtained based on geomorphological features, different illumination conditions and low spatial resolution. The achieved results proved the viability of using MIP and template matching by FFT, to detect impact craters from planetary surfaces.en
dc.description.affiliationSao Paulo State Univ, Dept Cartog, Presidente Prudente, Brazil
dc.description.affiliationSao Paulo State Univ, Dept Math & Comp Sci, Presidente Prudente, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Dept Cartog, Presidente Prudente, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Dept Math & Comp Sci, Presidente Prudente, Brazil
dc.description.sponsorshipPROPe
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdPROPe: 105/2015
dc.description.sponsorshipIdCAPES: 9022/13-9
dc.description.sponsorshipIdFAPESP: 2013/25257-4
dc.description.sponsorshipIdFAPESP: 2015/26743-5
dc.format.extent1306-1319
dc.identifierhttp://dx.doi.org/10.1080/19475705.2017.1327463
dc.identifier.citationGeomatics Natural Hazards & Risk. Abingdon: Taylor & Francis Ltd, v. 8, n. 2, p. 1306-1319, 2017.
dc.identifier.doi10.1080/19475705.2017.1327463
dc.identifier.fileWOS000418899200065.pdf
dc.identifier.issn1947-5705
dc.identifier.urihttp://hdl.handle.net/11449/163675
dc.identifier.wosWOS:000418899200065
dc.language.isoeng
dc.publisherTaylor & Francis Ltd
dc.relation.ispartofGeomatics Natural Hazards & Risk
dc.relation.ispartofsjr0,426
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectAutomatic detection
dc.subjectimpact craters
dc.subjectMars
dc.subjectmorphological image processing
dc.subjecttemplate matching
dc.titleImproved automatic impact crater detection on Mars based on morphological image processing and template matchingen
dc.typeArtigo
dcterms.licensehttp://journalauthors.tandf.co.uk/permissions/reusingOwnWork.asp
dcterms.rightsHolderTaylor & Francis Ltd
unesp.author.orcid0000-0001-6237-3070[2]
unesp.author.orcid0000-0002-7069-0479[3]

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Artigos - Cartografia - FCT
Artigos - Matemática e Computação - FCT