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dc.contributor.advisorRowe, Neil C.
dc.contributor.authorHerman, Jessica
dc.date.accessioned2012-08-09T18:48:19Z
dc.date.available2012-08-09T18:48:19Z
dc.date.issued2000-06
dc.identifier.urihttp://hdl.handle.net/10945/7805
dc.description.abstractAccurate identification of unknown contacts is a crucial issue in military intelligence. In order for this task to be accomplished by human observers, each one must be specially trained and regularly re-qualify. Even with training, their decisions are subject to human error: bias, expectations, or even a lack of sleep may compromise their accuracy. If an automated system could quickly and accurately determine the identity of a contact, it would be a great benefit. This thesis explores some of the problems which must be addressed in producing such a system. We detail an approach to an algorithm which compares a picture of an unknown ship to an established database and determines its most likely classification. In particular, we use infrared images from FLIR video taken at sea, and obtain classification results for a small test set. We tested eighteen images with success rates varying between seventy-three and eighty-nine percenten_US
dc.description.urihttp://archive.org/details/targetidentifica109457805
dc.format.extentvii, 57 p.;28 cm.en_US
dc.language.isoen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.titleTarget identification algorithm for the AN/AAS-44V Forward Looking Infrared (FLIR)en_US
dc.typeThesisen_US
dc.contributor.secondreaderBaer, Wolfgang
dc.subject.authorImage recognitionen_US
dc.subject.authorship identificationen_US
dc.subject.authorHough transformen_US
dc.subject.authoredge detectionen_US
dc.description.serviceEnsign, United States Navyen_US
etd.thesisdegree.nameM.S. in Computer Scienceen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineComputer Scienceen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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