Radial moments for invariant image analysis: computational and statistical aspects

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dc.contributor.authorSamanta, Urmila
dc.contributor.examiningcommitteePeters, James (Electrical and Computer Engineering) Liao, Simon (Applied Computer Science, University of Winnipeg)en_US
dc.contributor.supervisorPawlak, Miroslaw (Electrical and Computer Engineering)en_US
dc.date.accessioned2013-08-22T14:22:27Z
dc.date.available2013-08-22T14:22:27Z
dc.date.issued2013-08-22
dc.degree.disciplineElectrical and Computer Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractZernike moments are sets of mathematical quantities that uniquely characterize an image. It is known that they are invariant under rotation and reflection and robust to noise. In this thesis several other algorithms have been used to calculate these moments. The intent of this thesis is: 1. to use the classical method and the algorithms to reconstruct an image using Zernike moments and study their accuracy and 2. to examine if the invariance and noise insensitivity property of the calculated Zernike moments are upheld by these procedures. It is found that the constructed images using these algorithms do not resemble the original image. This prevents us from carrying out further study of these algorithms. The classical method has been successfully used to reconstruct an image when the height and width are equal. The classical method is also shown to be invariant under rotation and reflection and robust to Poisson noise. xxxviien_US
dc.description.noteOctober 2013en_US
dc.identifier.urihttp://hdl.handle.net/1993/22062
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectZernike Momentsen_US
dc.subjectImage Reconstructionen_US
dc.subjectInvariance Propertiesen_US
dc.titleRadial moments for invariant image analysis: computational and statistical aspectsen_US
dc.typemaster thesisen_US
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