Vehicle Number Plate Recognition Using Raspberry Pi

Modern intelligent transportation systems heavily rely on automatic vehicle licence plate recognition (ITS). Typically, there are four processes involved in recognising a car licence plate: extracting the licence plate from an image, character segmentation, and character recognition.

An image of the licence plate is taken using a camera mounted over an exposure system, and the image is then processed to extract the licence number. Numerous applications, including electronic payment systems for tolls, parking fees, and freeway and arterial monitoring systems for traffic surveillance, can use the extracted information with or without a database.

A vehicle’s licence number is taken if it attempts to violate the traffic laws, and details about the infraction and the licence plate number are given to the Traffic Control Section for additional legal action to be taken. To alert the on-field police officer to the crime, an alarm is triggered. Additionally, it must to be generalised to handle plates from various countries, provinces, or states.

Hardware Specifications

  • Raspberry Pi 3
  • LCD Display
  • Buzzer
  • Resistors
  • Capacitors
  • Transistors
  • Cables and Connectors
  • Diodes
  • PCB and Breadboards
  • LED
  • Transformer/Adapter
  • Push Buttons
  • Switch
  • IC
  • IC Sockets
  • Camera

Software Specifications

  • Linux OS
  • Programming Language: Python

Block Diagram

Here, we suggest a Raspberry Pi-based car number plate recognition system that uses image processing to recognise licence plates automatically. The device makes use of an LCD display circuit connected to a Raspberry Pi and a camera. Incoming camera footage is continuously processed by the system to look for any signs of number plates. When the camera detects a number plate in front of it, it analyses the camera input and removes the number plate portion from the image. uses OCR to process the recovered image and separate the licence plate number from it. The extracted number is subsequently shown on an LCD display by the system. As a result, we proposed a Raspberry Pi-based, fully functional car number plate recognition system.


  • High Efficient
  • High accuracy
  • Automatic process


  • Toll payment applications
  • Parking fee applications
  • Traffic sureillance applications

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