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dc.contributor.advisorYan, Wei qi
dc.contributor.authorLi, Piyuan
dc.date.accessioned2018-02-04T22:32:00Z
dc.date.available2018-02-04T22:32:00Z
dc.date.copyright2018
dc.identifier.urihttp://hdl.handle.net/10292/11150
dc.description.abstractThe focus of this thesis is on reliable and robust license plate recognition (LPR). The technology is currently in operation that both the quantity and quality-based approaches are needed. The entire procedure of license plate recognition consists of six steps: (1) image acquisition, (2) image pre-processing, (3) plate locating, (4) character segmentation, (5) character recognition, (6) output. However, when a road is uneven and slant, a vehicle will be shaky while running; consequently, the plate is also unstable and tilted with an angle of rotation at this moment. Meanwhile, a surveillance camera is very difficult to capture an effective image so that the plate is hard to be located and recognized. Due to this existing problem, the contributions of this thesis are: (1) plate tilt correction using Hough transform; (2) GNN-based plate number recognition. The novelties of this thesis are to improve the robustness and reliability of license plate recognition through literature review as well as evaluate those existing technologies.en_NZ
dc.language.isoenen_NZ
dc.publisherAuckland University of Technology
dc.subjectPlate number recognitionen_NZ
dc.subjectImage rotationen_NZ
dc.subjectGNNen_NZ
dc.subjectImage correctionen_NZ
dc.subjectCharacter recognitionen_NZ
dc.titleRotation correction for license plate recognitionen_NZ
dc.typeThesisen_NZ
thesis.degree.grantorAuckland University of Technology
thesis.degree.levelMasters Theses
thesis.degree.nameMaster of Computer and Information Sciencesen_NZ
dc.rights.accessrightsOpenAccess
dc.date.updated2018-02-04T11:55:35Z


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