Near sets in pattern similarity distance based classification

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dc.contributor.authorVafabakhsh, Diba
dc.contributor.examiningcommitteeHo, Carl (Electrical and Computer Engineering) Wang, Luming (Asper School of Business)en_US
dc.contributor.supervisorPeters, James F. (Electrical and Computer Engineering)en_US
dc.date.accessioned2018-01-17T19:15:17Z
dc.date.available2018-01-17T19:15:17Z
dc.date.issued2018
dc.degree.disciplineElectrical and Computer Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractThis research is focused on studying the nearness theory, various neighbourhoods of points in proximity spaces and similarity measures which leads to discovering the set patterns in digital images. The problem considered in this thesis is set pattern discovery using topology of digital images and nearness theory and then using the extracted set patterns as the basis for the classification method that is introduced. Visual pattern is the repetition of some forms in a digital image. A visual set pattern is defined as a collection of sets that all of the members of the collection have common features and properties and are all descriptively near a given set called the pattern generator or motif set which itself is a bounded descriptive neighbourhood of a distinguished point of interest in the image. Using the generated set patterns, a classification method is introduced based on the set patterns similarity distance.en_US
dc.description.noteMay 2018en_US
dc.identifier.urihttp://hdl.handle.net/1993/32850
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectNearness theoryen_US
dc.subjectNeighbourhoodsen_US
dc.subjectProximity spaceen_US
dc.subjectfeature vectoren_US
dc.subjectProbe functionen_US
dc.subjectSpatialen_US
dc.subjectDescriptiveen_US
dc.subjectSet patternen_US
dc.subjectSet pattern generationen_US
dc.subjectMotifen_US
dc.subjectPatternen_US
dc.subjectPattern recognitionen_US
dc.subjectSimilarity Measureen_US
dc.subjectPattern similarity distanceen_US
dc.subjectSaliencyen_US
dc.subjectClassificationen_US
dc.titleNear sets in pattern similarity distance based classificationen_US
dc.typemaster thesisen_US
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