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dc.contributor.advisorTheoharis, Theoharisnb_NO
dc.contributor.advisorAamodt, Agnarnb_NO
dc.contributor.authorEliassen, Lars Molandnb_NO
dc.date.accessioned2014-12-19T13:38:53Z
dc.date.available2014-12-19T13:38:53Z
dc.date.created2012-11-08nb_NO
dc.date.issued2012nb_NO
dc.identifier565949nb_NO
dc.identifierntnudaim:6995nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/252933
dc.description.abstractCounting and classifying fish moving upstream in rivers to spawn is a useful way of monitoring the population of different species. Today, there exist some commercial solutions, along with some research that addresses the area. Case-based reasoning is a process that can be used to solve new problems based on previous problems. This thesis studies the possibilities of combining image processing techniques and case-based reasoning to classify species of fish which are similar to each other in both shape, size and color. Methods for image preprocessing are discussed, and tested. Methods for feature extraction and a case-based reasoning prototype are proposed, implemented and tested with promising results.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for datateknikk og informasjonsvitenskapnb_NO
dc.subjectntnudaim:6995no_NO
dc.subjectMTDT datateknikkno_NO
dc.subjectIntelligente systemerno_NO
dc.titleAutomatic Fish Classification: Using Image Processing and Case-Based Reasoningnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber89nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskapnb_NO


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