Near Sets in Set Pattern Classification

Simple item page
dc.contributor.authorUchime, Chidoteremndu Chinonyelum
dc.contributor.examiningcommitteeAlfa, Attahiru (Electrical and Computer Engineering) Leung, Carson (Computer Science)en_US
dc.contributor.supervisorPeters, James (Electrical and Computer Engineering)en_US
dc.date.accessioned2015-02-06T21:46:32Z
dc.date.available2015-02-06T21:46:32Z
dc.date.issued2015-02-06
dc.degree.disciplineElectrical and Computer Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractThis 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.description.noteMay 2015en_US
dc.identifier.urihttp://hdl.handle.net/1993/30264
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectpatternen_US
dc.subjectpattern generationen_US
dc.subjectpattern recognitionen_US
dc.subjectproximity spaceen_US
dc.subjectvisual set patternen_US
dc.subjectmotif patternen_US
dc.subjectseed motifen_US
dc.subjectdescriptionen_US
dc.subjectperceptionen_US
dc.subjectprobe functionen_US
dc.subjectfeature vectoren_US
dc.subjectbinary classificationen_US
dc.subjectK-meansen_US
dc.subjectCBIRen_US
dc.subjectsalienten_US
dc.subjectsimilarity measureen_US
dc.subjectsensitivityen_US
dc.subjectspecificityen_US
dc.titleNear Sets in Set Pattern Classificationen_US
dc.typemaster thesisen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Uchime_Chidoteremndu.pdf
Size:
3.63 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
2.25 KB
Format:
Item-specific license agreed to upon submission
Description:
Download
Collections
FGS - Electronic Theses and Practica