Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor | Multi-disciplinary Studies | en_US |
dc.creator | Lau, Kam-sun | - |
dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/366 | - |
dc.language | English | en_US |
dc.publisher | Hong Kong Polytechnic University | - |
dc.rights | All rights reserved | en_US |
dc.title | Development of a window based vision system for detection of vehicle license plate | en_US |
dcterms.abstract | In this report, a system for the detection of vehicle license plates is presented. The vehicle image is captured by a video camera and then digitized by a Video Blaster to BMP file format. The system locates the vehicle license plate. The vehicle information and the vehicle license plate image are transmitted and stored in remote database for later retrieval. The segmentation algorithm we used is based on grey scale morphological operations to detect the region of a vehicle license plate from an image. The algorithm proposed in this report is based on grey scale morphological operations and detects the features in license plates such as horizontal lines, and spacing between characters, without any specific restrictions on the input images. The robustness of this algorithm is demonstrated by using images in noisy conditions and poor illumination. The aim of the system is to read automatically the license number of a car from a camera placed at the road side, tunnel entrance or car park for security, traffic monitoring or recording purposes. It is found to be useful in monitoring systems such as automated toll-pay systems, identification of stolen vehicles, travel time data provision or in parking lots. | en_US |
dcterms.extent | v, 95 leaves : ill. (some col.) ; 30 cm | en_US |
dcterms.isPartOf | PolyU Electronic Theses | en_US |
dcterms.issued | 1997 | en_US |
dcterms.educationalLevel | All Master | en_US |
dcterms.educationalLevel | M.Sc. | en_US |
dcterms.LCSH | Automobile license plates -- Identification | en_US |
dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
dcterms.accessRights | restricted access | en_US |
Files in This Item:
File | Description | Size | Format | |
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b12504543.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 7.31 MB | Adobe PDF | View/Open |
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