Electronic toll collection system using computer vision plate number recognition

• Main Authors: De Guzman, Ed Lorence R., Natividad, Sean Francis M., Ulanday, Mikhail C.
• Format: text
• Language: English
• Published: Animo Repository 2016
• Subjects: Electronic traffic controls; Toll roads > Automation; Motor vehicles; Traffic congestion > Management; Electrical and Electronics
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/7219
• Institution: De La Salle University

Heavy traffic is one of the increasing major problems that the country is facing. Brian Galagnara, president of a group of concerned citizens advocating Respect Equals Discipline on Philippine roads called Red Advocates, said that according to a 1999 study made by Japan International Cooperation Agency (JICA) and Department of Transportation and Communications (DOTC) supported by a 2011 study made by the University of the Philippines National Center for Transportation Studies (UP NCTS), the Philippines has a 140 billion peso loss due to traffic congestion in Metro Manila. The quantification of such loss are the direct losses due to wasted gasoline, wasted electricity, employment of traffic aides, and lost labor hours and indirect losses of missed business opportunities, withdrawal of potential foreign investment, and reduced capital inflow (2Metro Manila traffic costs P140B a year,3 2013). Even if there is an existing ETC system, most people still does not avail it because it is costly with a subscription fee of PHP 1,700.00. The primary purpose of this paper is to integrate a method that would eliminate the need of the use of ticket cards and RFID tags and Electronic Toll Collection On-board units and utilize what the motorists already have – that is the plate numbers of their cars as a replacement, thus introducing the use of Automatic Plate Number / Number Plate Recognition (APNR/ANPR). This also aims to remove the use of boom barriers for the motorists to avoid stopping at the given toll gates in order to have a continuous traffic flow. The APNR system will be based on the use of computer vision which utilizes the OpenCV library to process systems such as Car detection, Plate detection, Plate Localization, and Plate number recognition. Once the system has been able to tag the vehicle by identifying the plate number the information gathered will be passed to the ETC system. The ETC system is handled by a software called Microsoft Access for querying, storing, and maintaining. Lastly all the systems discussed above will be integrated thru a simple GUI that will handle all the processes required.