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dc.contributor.authorJia, Wanru
dc.date.accessioned2020-12-15T19:03:06Z
dc.date.available2020-12-15T19:03:06Z
dc.date.issued2020-12-15T19:03:06Z
dc.identifier.urihttp://hdl.handle.net/10222/80102
dc.description.abstractThis thesis developed two sophisticated statistical methods for edge detection in X-ray images. The first method evaluates the possibility of each pair of pixels in the X-ray images being on the intended edges by assigning a calculated goodness score to each pair. To further improve the quality of edge detection, another method was developed to obtain higher accuracy and precision by getting thinner and more continuous edges. The second method carries out edge detection by tracing the progression of edges from certain starting points. Both of these methods shows better results than two state-of-the-art methods.en_US
dc.language.isoenen_US
dc.subjectEdge Detectionen_US
dc.subjectHessian Matricesen_US
dc.subjectX-Ray Imagesen_US
dc.titleEdge Detection Operators for X-ray Images Based on Hessian Matricesen_US
dc.date.defence2020-12-08
dc.contributor.departmentDepartment of Mathematics & Statistics - Statistics Divisionen_US
dc.contributor.degreeMaster of Scienceen_US
dc.contributor.external-examinern/aen_US
dc.contributor.graduate-coordinatorJOANNA MILLS FLEMMINGen_US
dc.contributor.thesis-readerLam Hoen_US
dc.contributor.thesis-readerAndrew Irwinen_US
dc.contributor.thesis-supervisorHong Guen_US
dc.contributor.thesis-supervisorToby Kenneyen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.manuscriptsNot Applicableen_US
dc.contributor.copyright-releaseNot Applicableen_US
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