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dc.contributor.advisorYu, Weihai
dc.contributor.advisorJøkulsson, Gudmundur
dc.contributor.authorJacobsen, Joakim
dc.date.accessioned2013-10-02T12:36:39Z
dc.date.available2013-10-02T12:36:39Z
dc.date.issued2013-05-15
dc.description.abstractEven with today's technologies many tasks relies on humans to be completed correctly. Engineers must monitor steps in large chains of operations, and verify the results before the next process is allowed to continue. In many such systems, a lot of useful data passes by without ever been stored for efficient future usage. Even though some operations must be verified by an experienced human eye, many, if not all, could benefit from computed assistance. When processing satellite imagery there are a lot of steps involved before there is a final product. This thesis examines one specific part of the process, how to determine if a feature observed is permanent or not. A self learning geographical information system implementation that can determine the state of specific features will be presented. The system is capable of filtering out permanent installations from vessel traffic in highly dense areas. Further we'll see that with such a system at the core, other useful functionality can easily be extended on top of it. Such functionality could be tracking of vessels, oil spills or ice floes, the latter two which have been implemented. With such a system at hand, the day to day tasks of engineers monitoring satellite observations can be made easier and less error prone. In addition such a historical view of the data can help with improving existing services as well as those still under development.en
dc.identifier.urihttps://hdl.handle.net/10037/5433
dc.identifier.urnURN:NBN:no-uit_munin_5134
dc.language.isoengen
dc.publisherUniversitetet i Tromsøen
dc.publisherUniversity of Tromsøen
dc.rights.accessRightsopenAccess
dc.rights.holderCopyright 2013 The Author(s)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/3.0en_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)en_US
dc.subject.courseIDINF-3990en
dc.subjectpermanent feature filteringen
dc.subjectmaritime traffic and installationsen
dc.subjectchange detectionen
dc.subjectremote sensingen
dc.subjectvessel detectionen
dc.subjecttracking of moving featuresen
dc.subjectspatiotemporal databasesen
dc.subjectspatial filteringen
dc.subjecttemporal topologyen
dc.subjectVDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation, visualization, signal processing, image processing: 429en
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Simulering, visualisering, signalbehandling, bildeanalyse: 429en
dc.titleFeature Detector: a support system for tracking satellite detected dynamic and permanent featuresen
dc.typeMaster thesisen
dc.typeMastergradsoppgaveen


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Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)