dc.contributor.author | Jia, Wanru | |
dc.date.accessioned | 2020-12-15T19:03:06Z | |
dc.date.available | 2020-12-15T19:03:06Z | |
dc.date.issued | 2020-12-15T19:03:06Z | |
dc.identifier.uri | http://hdl.handle.net/10222/80102 | |
dc.description.abstract | This 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.iso | en | en_US |
dc.subject | Edge Detection | en_US |
dc.subject | Hessian Matrices | en_US |
dc.subject | X-Ray Images | en_US |
dc.title | Edge Detection Operators for X-ray Images Based on Hessian Matrices | en_US |
dc.date.defence | 2020-12-08 | |
dc.contributor.department | Department of Mathematics & Statistics - Statistics Division | en_US |
dc.contributor.degree | Master of Science | en_US |
dc.contributor.external-examiner | n/a | en_US |
dc.contributor.graduate-coordinator | JOANNA MILLS FLEMMING | en_US |
dc.contributor.thesis-reader | Lam Ho | en_US |
dc.contributor.thesis-reader | Andrew Irwin | en_US |
dc.contributor.thesis-supervisor | Hong Gu | en_US |
dc.contributor.thesis-supervisor | Toby Kenney | en_US |
dc.contributor.ethics-approval | Not Applicable | en_US |
dc.contributor.manuscripts | Not Applicable | en_US |
dc.contributor.copyright-release | Not Applicable | en_US |