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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/38262
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dc.contributor.authorDal Poz, A. P.-
dc.contributor.authorTommaselli, AMG-
dc.contributor.authorSadjadi, F. A.-
dc.date.accessioned2014-05-20T15:28:28Z-
dc.date.accessioned2016-10-25T18:03:30Z-
dc.date.available2014-05-20T15:28:28Z-
dc.date.available2016-10-25T18:03:30Z-
dc.date.issued1998-01-01-
dc.identifierhttp://dx.doi.org/10.1117/12.323861-
dc.identifier.citationAutomatic Target Recognition Viii. Bellingham: Spie-int Soc Optical Engineering, v. 3371, p. 436-447, 1998.-
dc.identifier.issn0277-786X-
dc.identifier.urihttp://hdl.handle.net/11449/38262-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/38262-
dc.description.abstractThe identification of ground control on photographs or images is usually carried out by a human operator, who uses his natural skills to make interpretations. In Digital Photogrammetry, which uses techniques of digital image processing extraction of ground control can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features of object space and its homologous in the image space. A build-in self-diagnosis is also used in this method. It is based on implementation of data snooping statistic test in the process of spatial resection using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.en
dc.format.extent436-447-
dc.language.isoeng-
dc.publisherSpie - Int Soc Optical Engineering-
dc.sourceWeb of Science-
dc.subjectphotogrammetrypt
dc.subjectvisionpt
dc.subjectautomationpt
dc.subjectmatchingpt
dc.subjectmodelingpt
dc.subjectpatternpt
dc.titleStrategy to detect ground control in digital imagesen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationSão Paulo State Univ, BR-19060900 Presidente Prudente, SP, Brazil-
dc.description.affiliationUnespSão Paulo State Univ, BR-19060900 Presidente Prudente, SP, Brazil-
dc.identifier.doi10.1117/12.323861-
dc.identifier.wosWOS:000076932900044-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofAutomatic Target Recognition Viii-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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