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dc.contributor.advisorChu, Peter C.
dc.contributor.advisorFan, Chenwu
dc.contributor.authorFritz, James R.
dc.dateDec-13
dc.date.accessioned2014-02-18T23:38:55Z
dc.date.available2014-02-18T23:38:55Z
dc.date.issued2013-12
dc.identifier.urihttp://hdl.handle.net/10945/38932
dc.descriptionApproved for public release; distribution is unlimited.en_US
dc.description.abstractThere have been three times more attacks to naval ships using sea mines than all other forms combined. Sea mines have always been viewed upon as underhanded and unchivalrous, yet they provide a weaker navy the capability to stall and damage a vastly superior navy. Utilizing unmanned sensors to detect sea mines is the goal of the navy for the future. Computer-aided detection (CAD) of sea mines is much faster and more consistent than a human operator, yet it is not currently being utilized by any of our mine countermeasure assets. Although there are many studies that have incorporated computer aided detection and classification algorithms with sonar imagery for mine warfare, few have used Light Detection and Ranging (LIDAR). During an amphibious assault scenario the ability to land assets quickly and mitigate risk is vital to the success. This thesis analyzes Rapid Overt Aerial Reconnaissance data from an Office of Naval Research experiment by Fort Walton Beach, FL. The CAD algorithm that was developed consistently detects sea mines in LIDAR data while having a manageable false alarm rate.en_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United Statesen_US
dc.titleComputer-aided detection of rapid, overt, airborne, reconnaissance data with the capability of removing oceanic noisesen_US
dc.typeThesisen_US
dc.contributor.secondreaderBetsch, Ronald E.
dc.contributor.departmentOceanography
dc.subject.authorMine Countermeasuresen_US
dc.subject.authorComputer Aided Detectionen_US
dc.subject.authorComputer Aided Identificationen_US
dc.subject.authorOptimizationen_US
dc.subject.authorPhysical Oceanographyen_US
dc.description.serviceLieutenant, United States Navyen_US
etd.thesisdegree.nameMaster of Science in Joint Meteorology and Physical Oceanographyen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineJoint Meteorology and Physical Oceanographyen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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