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dc.contributor.supervisor Peters, James (Electrical and Computer Engineering) en_US
dc.contributor.author Uchime, Chidoteremndu Chinonyelum
dc.date.accessioned 2015-02-06T21:46:32Z
dc.date.available 2015-02-06T21:46:32Z
dc.date.issued 2015-02-06
dc.identifier.uri http://hdl.handle.net/1993/30264
dc.description.abstract This research is focused on the extraction of visual set patterns in digital images, using relational properties like nearness and similarity measures, as well as descriptive properties such as texture, colour and image gradient directions. The problem considered in this thesis is application of topology in visual set pattern discovery, and consequently pattern generation. A visual set pattern is a collection of motif patterns generated from different unique points called seed motifs in the set. Each motif pattern is a descriptive neighbourhood of a seed motif. Such a neighbourhood is a set of points that are descriptively near a seed motif. A new similarity distance measure based on dot product between image feature vectors was introduced in this research, for image classification with the generated visual set patterns. An application of this approach to pattern generation can be useful in content based image retrieval and image classification. en_US
dc.subject pattern en_US
dc.subject pattern generation en_US
dc.subject pattern recognition en_US
dc.subject proximity space en_US
dc.subject visual set pattern en_US
dc.subject motif pattern en_US
dc.subject seed motif en_US
dc.subject description en_US
dc.subject perception en_US
dc.subject probe function en_US
dc.subject feature vector en_US
dc.subject binary classification en_US
dc.subject K-means en_US
dc.subject CBIR en_US
dc.subject salient en_US
dc.subject similarity measure en_US
dc.subject sensitivity en_US
dc.subject specificity en_US
dc.title Near Sets in Set Pattern Classification en_US
dc.degree.discipline Electrical and Computer Engineering en_US
dc.contributor.examiningcommittee Alfa, Attahiru (Electrical and Computer Engineering) Leung, Carson (Computer Science) en_US
dc.degree.level Master of Science (M.Sc.) en_US
dc.description.note May 2015 en_US


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