VEHICLE LICENSE PLATE RECOGNITION USING ARTIFICIAL NEURAL NETWORK WITH OTP VERIFICATION GATE CONTROL SYSTEM

Electronics and Communication Engineering

NATIONAL CONFERENCE on VLSI, COMMUNICATION AND SIGNAL PROCESSING (NCVCS-2017)

In this paper, License plate recognition (LPR) is presented. License plate Recognition System(LPRS) plays a vital role in small city initiatives such as traffic control, smart parking ,toll management and security. Automatic Number Plate Recognition (ANPR) is an image-processing technology and an important field of research that identifies vehicles by their number plates in which the number plate information is extracted from vehicle's image or from sequence of images without direct human intervention. It is used for real time application and it has to recognize the number plates of all types under different environmental condition. In this paper we propose a new method which is robust enough to recognize the characters from the number plates with the help of artificial neural network(ANN. The extracted license number plate is matched with the database to check the authorization of the vehicle. Once the authorization is confirmed in the software then the second level authorization is confirmed by sending the OTP (One Time Password) using GSM to the predefined mobile number. The received OTP has to be entered in the keypad connected to the microcontroller, once the entered OTP matches the sent then the Magnetic Coil connected to is unlocked otherwise it will be in the locked condition. The proposed vehicle license plate recognition using artificial neural networks and remote load operation recognizes the license plate robustly and it includes two level securities one is the authentication in the software and second one is OTP generation which will improve the security.

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