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Addis Ababa University Libraries Electronic Thesis and Dissertations: AAU-ETD! >
Faculty of Technology >
Thesis - Computer Engineering >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/2714
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| Title: | Design and Implementation of Car Plate Recognition System for Ethiopian Car Plates |
| Authors: | Huda, Zuber |
| Advisors: | Dr. Assefa Dagne |
| Keywords: | Optical Character Recognition (OCR),
Connected Component Analysis (CCA),
Plate region extraction |
| Copyright: | Nov-2011 |
| Date Added: | 6-May-2012 |
| Publisher: | AAU |
| Abstract: | During the past few years, Intelligent Transportation Systems (ITSs) have had a wide impact in
people’s life as their scope is to improve transportation safety and mobility and to enhance
productivity through the use of advanced technology. A growing demand for traffic data
concerning traffic flow and automatic car identification, led researchers around the world to
adopt advanced electronic and computer vision technologies to monitor and control traffic flow.
Increasing levels of road traffic needs real time analysis of a moving car in order to extract
important data, in this case the car plate number. Also, the incorporation of Optical Character
Recognition (OCR) with different applications created the ambition to replicate human tasks with
machines.
In this thesis, a car plate recognition system for Ethiopian vehicles is proposed, on the basis of
connected component analysis (CCA) for plate region extraction in conjunction with template
matching technique for character recognition. First the plate region is extracted and this image is
fed to the OCR. The system is simulated in Matlab, and performance is tested on real images.
The developed system was tested using 23 test images. The CPR system developed showed an
accuracy of 52.63%. Also a separate test was done on the plate region localization and the OCR
system. The result of the separate tests showed accuracy of 82.6% for the plate region
localization and 82.11% for the OCR. It is observed that the results are mainly influenced by the
quality of the input image and distance between the camera and the car. The experimental results
showed that by adjusting the influencing factors, the system can perform in a good way. |
| URI: | http://hdl.handle.net/123456789/2714 |
| Appears in: | Thesis - Computer Engineering
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