Section outline

  • Introduction to Computer Vision and OpenCV

    Computer vision is a field of artificial intelligence that enables machines to interpret and make decisions based on visual input—just like humans do using their eyes and brain. In robotics, this means equipping our robots with the ability to see, recognize, and react to objects, colors, shapes, and movements captured by a camera. This opens up powerful applications like line following, face detection, gesture control, and autonomous navigation.

    • What is OpenCV

      One of the most widely used tools in computer vision is OpenCV (Open Source Computer Vision Library). It is a highly efficient and flexible library written in C++ with Python bindings. OpenCV allows developers to perform a wide range of image processing tasks such as filtering, object detection, edge recognition, motion tracking, and more.

      Before we dive into using OpenCV, it's important to understand what it does under the hood. Every image or video is essentially a matrix of pixel values. These values define colors, brightness, and edges. Computer vision processes these pixel matrices to extract useful information. For example, if we want to detect a red ball, OpenCV can isolate red-colored pixels from a video feed, find the ball's outline, and track its movement across frames.

    • 👓 Uses of computer vision in robotics

      Let’s look at a few key uses of computer vision in robotics:

      • Color detection – Identify specific colors and take action when they appear.
      • Object tracking – Follow a moving item like a hand, ball, or light source.
      • Gesture control – Detect hand signs or body movements to control a robot.
      • Obstacle avoidance – Use vision to detect and avoid barriers in the path.

      In this course, we will use Python and OpenCV together to implement real-world computer vision tasks for robotics. By the end, you will be able to build your own robot that sees, thinks, and reacts to visual input.

      To get started, make sure you have a working installation of Python and OpenCV on your computer. If not, you can use the command below to install OpenCV via pip:

      pip install opencv-python

      We will also use additional tools like NumPy for matrix operations and matplotlib for image display when required.

       This foundational understanding of what computer vision is, and why OpenCV is the tool of choice, will set the stage for all the exciting hands-on sections that follow.