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Research Paper | Electronics & Communication Engineering | India | Volume 5 Issue 11, November 2016 | Rating: 6.4 / 10
Automatic Number Plate Recognition for use in Different Countries using Raspberry pi (Real Time Approach)
Radhika S. Dangare | Prof. G. D. Dalvi [2]
Abstract: The paper aims at designing a system which captures the image of the number plate automatically of a vehicle and these details were verified using Raspberry Pi processor for authentication. The system also alerts the authorities when any unauthorized image of number plate is detected using buzzer alarm system. Automation is the most frequently spelled term in the field of electronics. The hunger for automation brought many revolutions in the existing technologies. This paper makes use of an onboard computer, which is commonly termed as Raspberry Pi processor. It acts as heart of the project. This onboard computer can efficiently communicate with the output and input modules which are being used. The Raspberry Pi is a creditcard-sized single-board computer developed in the UK by the Raspberry Pi Foundation. The Raspberry Pi has a Broadcom BCM2835 system on a chip (SoC), which includes an ARM1176JZFS 700 MHz processor, Video Core IV GPU, and was originally shipped with 256 megabytes of RAM, later upgraded to 512 MB. It does not include a built-in hard disk or solid-state drive, but uses an SD card for booting and long-term storage. The device which is able to perform the task is a Raspberry Pi processor. When any vehicle passes by the system, the image of the number plate of every vehicle is captured using camera. The image of the number plate details are fed as input to the Raspberry Pi processor. The Processor takes responsibility to check the authentication details of every vehicle. Once the vehicle details are recognized then the processor op-erates the gate using stepper motor. The sys-tem also alerts the user through buzzer alarm whenever it detects an unauthorized image of number plate was detected. To perform this task, Raspberry Pi processor is programmed using embedded Linux. Index Termssoc, Raspberry Pi, Linux.
Keywords: Automatic Number Plate Recognition ANPR, Artificial Neural Network ANN, Number Plate, Optical Character Recognition, Raspberry Pi
Edition: Volume 5 Issue 11, November 2016,
Pages: 1719 - 1724