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dc.contributor.authorChiang, Pei-Jung Amy
dc.date.accessioned2016-06-29T21:22:44Z
dc.date.available2016-06-29T21:22:44Z
dc.date.issued2016-06-29
dc.identifier.citationChiang, Pei-Jung Amy. Legendre Moments Explorations via Image Reconstruction; A Thesis Submitted to the Faculty of Graduate Studies in Partial Ful.lment of the Requirements for the Degree of Master of Science. Winnipeg, Manitoba, Canada: University of Winnipeg, 2014.
dc.identifier.urihttp://hdl.handle.net/10680/1209
dc.descriptionA Thesis Submitted to the Faculty of Graduate Studies in Partial Ful.lment of the Requirements for the Degree of Master of Science, Department of Applied Computer Science, University of Winnipeg.en_US
dc.description.abstractLegendre Moment has been applied in image reconstruction since early years. In this research, a numerical integration method is proposed to improve the computational accuracy of Legendre moments. To clarify the improved computation scheme, image reconstructions from higher orders of Legendre moments, up to 240, are conducted. With the more accurate generated moments, the distributions of image information in a finite set of Legendre moments is investigated. We have concluded that each individual finite set of Legendre moments will represent the unique image features independently, while the even orders of Legendre moments describe most of image characteristics.en_US
dc.language.isoenen_US
dc.publisherUniversity of Winnipeg
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectLegendre Momentsen_US
dc.titleLegendre Moments Explorations via Image Reconstructionen_US
dc.typeThesisen_US
dc.description.degreeMaster of Science in Applied Computer Science
dc.publisher.grantorUniversity of Winnipeg
thesis.degree.disciplineApplied Computer Science
thesis.degree.levelmasters
thesis.degree.nameMaster of Science in Applied Computer Science
thesis.degree.grantorUniversity of Winnipeg


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