Computer vision: image shape geometry and classification

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dc.contributor.authorPham, Dat Hoang
dc.contributor.examiningcommitteeMcLeod, Robert D (Electrical and Computer Engineering) Thulasiram, Ruppa (Computer Science)en_US
dc.contributor.supervisorPeters, James (Electrical and Computer Engineering)en_US
dc.date.accessioned2019-02-06T20:55:23Z
dc.date.available2019-02-06T20:55:23Z
dc.date.issued2018-09en_US
dc.date.submitted2019-01-23T15:55:11Zen
dc.degree.disciplineElectrical and Computer Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractThis research introduces the study of shape analysis with shape descriptors based on the geometry of image triangulation. The Delaunay approach is used to superimposes on an image with a mesh filled with various sized triangles that give rise to various simplexes. In its simplest form, a simplex is a collection of path-connected vertices. The motivation for this approach in image analysis is that Delaunay triangulation covers image shapes having unknown geometries with simplexes that have known geometries that we can measure and compare. This approach provides the foundation for the study of image shape geometry and the extraction of features for many applications in computer vision such as image processing, image segmentation, object recognition and classification. Shape descriptors are constructed with features extracted from the geometry of the simplexes covering planar images. In this research, shape descriptors provide a framework for tracking the persistence tolerance of a shape over sequences of image captured my camera. An application that can be benefit from this approach is video content retrieval and classificationen_US
dc.description.noteFebruary 2019en_US
dc.identifier.urihttp://hdl.handle.net/1993/33748
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectComputer vision, Content-based image retrieval(CBIR), Description, Feature vector, Shape descriptor, Persistence, Classification, Delaunay triangulation, Similarity measure, Persistence measure, Shape analysis, Video content retrieval.en_US
dc.titleComputer vision: image shape geometry and classificationen_US
dc.typemaster thesisen_US
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