pip3 install opencv-contrib-python=4.1.0.25 sudo apt-get install libhdf5-dev -y sudo apt-get install libhdf5-serial-dev –y sudo apt-get install libatlas-base-dev –y sudo apt-get install libjasper-dev -y sudo apt-get install libqtgui4 –y sudo apt-get install libqt4-test –yĪfter that, use the below command to install the OpenCV on your Raspberry Pi. Then use the following commands to install the required dependencies for installing OpenCV on your Raspberry Pi. To install the OpenCV, first, update the Raspberry Pi. Here OpenCV library is used to detect and recognize faces. We previously used OpenCV in Face Recognition using the Raspberry Pi project. So before proceeding further, first install the OpenCV, Tesseract, and other required libraries.

Here we use the OpenCV library to detect and recognize number plates, and the Tesseract library is used to read the characters. Pre-requisites for Number Plate Recognition OpenCV Python To learn more about how to interface Pi camera with Raspberry Pi, follow our previous tutorial.

We previously used Pi camera with Raspberry pi, and built few projects using it like Web Controlled Raspberry Pi Surveillance Robot, IoT based Smart Wi-Fi doorbell, Smart CCTV Surveillance System, etc. Here only Raspberry Pi and Pi camera are used to build this Raspberry Pi Plate Recognition System. And finally, Raspberry Pi crops out that particular area and perform optical character recognition to read the license plate numbers. Then it uses the contour function from OpenCV to detect the license plate. Pi camera module continuously captures the frames, and when a key is pressed on the keyboard, it saves the last frame as a new image. This system automatically recognizes and reads vehicle license plates using OpenCV and Optical Character Recognition. So in this tutorial, we are going to build a Real-Time License Plate Recognition System using Raspberry Pi and Pi Camera.

Raspberry pi mpeg license key generator