A Duplicate number plate detection system using fixed location cameras
Kibunja, Kelvin Peter
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Vehicle registration is a legal necessity to all, any vehicle purchased must be registered and the purpose of this registration is to assist in vehicle identification. The vehicle identifier is usually a metal or plastic plate patched on the front or rear part of a vehicle and contains unique alphanumeric characters. If vehicles on the road do not have any unique identifying tags or have the wrong tags, people will have, an opportunity to be mischievous as no one will be able to identify or account for any vehicle. Hence, through vehicle registration one can be able to identify and prove ownership of the vehicle. In order to hide the identity vehicles are disguised by cloning the number plates which aids in providing inaccurate ownership details. Without the correct ownership details, it is difficult to trace any vehicle involved in an illegal activity be it theft, terrorism, to mention but a few. In Kenya for people to discover that a vehicle has duplicate number late, the vehicle must have attracted the police attention, and this could be through being involved in an illegal activity. This system of number plate identification is usually a posterior to a crime, and it entails conducting a search with the Kenya National Transport Safety Authority (NTSA). In a country like Britain, the system in place to identify number plates is a deterrent one, whereby fixed location cameras capture images of vehicle’s number plates then compare with what is in their regional registration database. In Kenya this system would work perfectly well but in cases where we have duplicates it will be an issue since it will be difficult to flag out one. To curb the problem, the researcher intends to use fixed location cameras to identify duplicate number plates. From the image, the system extracts the vehicle number plate, colour and model. Time and location of the image capture is recorded, and this will assist in comparison of the details captured. The researcher uses image processing and artificial neural network in identifying the colour and model of the vehicle. Prototyping methodology and analysis approach is used in developing the model as it allows development of independent modules on large scale applications.