20+ Raspberry Pi Tutorials in Computer Vision

Engineers have always tried to give the robot the gift of sight. So, they have to replicate the human vision process with computers, algorithms, cameras and more.

In the DIY area, a Raspberry Pi is the queen of prototyping platforms. It’s useful in different areas and for a large variety of applications. So, why not to use it in computer vision applications. The projects started coming fast and furious for navigation, localization, recognition, classifications, monitoring, reading and more.

There is virtually no limit what can be done with a single board computer, a camera module, a vision library such as OpenCV and a bit of creativity.

As you will see from the tutorials explored in this article, some of the most popular applications in computer vision deals with the detection, tracking and the recognition of objects and humans. Whether you are looking to build a robot able to detect a human or an automated system able to detect an object, the Raspberry Pi board is the center of your project.

From this collection of hand-picked tutorials, you will learn all kinds of tricks that can be applied to build simple and cost effective computer vision applications based on Pi.

Navigation and Obstacles Avoidance

  • Navigation to a target
    On the bigfacerobotics, Peter Neal shows us in a tutorial how to build an autonomous robot able to navigate to a target by detecting the coloured border of an image.
  • Programming a Raspberry Pi Robot Using Python and OpenCV
    In this project, the designer looking to make an autonomous robot with the py_websockets_bot library. The Python library communicates with the mobile robot over a network interface and sends commands that control the movements of the robot.
  • The RR.O.P. – RaspRobot OpenCV Project
    This Raspberry Pi robot uses the shapes, colors and textures of the objects to interact with the external environment.
  • Final Project Car Lab
    In this project, the designers build a computer vision application to avoid obstacles on a wide path defined by black parallel lines.
  • OpenCV and python for a line follower
    With a webcam, the OpenCV library, Python and a Raspberry Pi board, you can build a line follower robot using computer vision algorithms.
  • Obstacle detection using OpenCV
    In this tutorial, the designer uses four steps to detect obstacles in front of the robot. The first step is to capture an image. The second step is to convert the image into a grayscale image. The third step is to blur it slightly, and in the fourth step uses canny edge detection to highlight the edges in the image.
  • Autonomous bottle recycling robot
    In this tutorial, you can find how to build an eco-friendly robot engineered to avoid obstacle until the camera detects and recognizes a bottle.Tracking and Recognition

You may be interested in the following Raspberry Pi resources as well:
The Raspberry Pi camera guide


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