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|Title:||Automated Vehicle Administration System for Highways|
Research Subject Categories::TECHNOLOGY
|Abstract:||Throughout modernization, people have been looking for much more efficient methods of transportation to cope up with their busy schedules. They want to spend as less time on the road and reach the destination as fast and as efficiently as possible. This need made forward the concept of highways. Through the recent increase in vehicles in the island, the roads become congested, and this specially applies to the usage of main and predominant roads such as Galle road. Therefore, to cope with the demands, the highway concept has been implemented in Sri Lanka as well. The southern highway has been built and is in the process of building another one as well. With this development, a mechanism is needed in order to use the highway effectively and efficiently with its increase of use by means of incorporating a license plate detection and identification system. Due to the growing demand for the Automatic license plate recognition is a very applicable tool and can be used in automating toll booths, and providing security. Some of the many instances where automatic license plate detection provides added convenience are in automatically charging a driver’s bank account/credit card (CC) instead of having to stop and pay and guaranteeing security on the roads by monitoring usage and criminal activities. Automated highway system will also enable the gathering statistical data such as the movements of traffic and usage. This research involved with using features in the image and image processing algorithms to filter the input image and localize license plate. Once identified the use of Optical Character Recognition (OCR) tool to extract the alpha-numeric characters of the license plate and used as a input for the entire system. The system can be used as method of electronic toll collection and enabling automated usage of the highway in a much more efficient manner as described in this paper. The combination of all these aspects will compromise the automated highway control system that is researched, described and implemented in this project. According to the results gathered it can be seen that the image processing and extraction methods were successful in identifying vehicles and also low response times prove the system has high performance as well. Improving the OCR tool by configuring its neural network and enhancing its success rate and use of online interface for users and implementation of image clarification techniques to improve image visibility was identified as good improvements to system.|
|Appears in Collections:||Master of Computer Science - 2013|
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