Abstract— Day by day India’s population is swarming and undoubtedly it is second highest population in the world. If population increases day by day automatically number of vehicles will be increased so much it is very much desperate to keep track of each vehicle for traffic management. Automatic number plate recognition is used to collecting toll amount without man power, and it allows following traffic rules. Online remuneration system at tollbooth automation is unique. Automatic number plate recognition algorithm does not detect the number plate if dust accumulated on it. This can be overcome by using online remuneration system at tollbooth automation. In existing system toll collection of vehicle is done manually till the completion of each vehicles transaction, rest of the vehicles have to wait this leads to a more traffic, wastage of time and its prone to human errors. The proposed paper suggests an automated way of high way toll collection based on the number plate of the vehicle when it passes through a toll collection booth. It detects vehicle number and compare with vehicular database. That determines the status of the vehicle and if vehicle is owned, it deducts the toll amount from the owners account and send message to the owners mobile. In case of theft, the particular block listed vehicle will not be allowed to pass through toll gate. A corresponding message will be sent to owner's mobile and highway patrol. A Copy of all this transaction stored in web server and distributed to all server. This information stored between host system and testing equipment for data transfer. This project enhances the performance of the system up to maximum extent possible with less efforts and use of computational resources.

Index Terms— License plate, Canny edge detection, ANPR, Non maximal suppression, Morphological image, GSM

Cite: Shilpa P A and Chinna V Gowdar, "ONLINE REMUNERATION SYSTEM AT TOLL BOOTH AUTOMATION," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 4, No. 3, pp. 31-39, July 2015.