Raspberry Pi Computer Vision Programming, Second Edition

Computer Vision on a Tiny Computer 🍓

The Raspberry Pi makes computer vision tangible. Instead of treating image processing as an abstract exercise, this book shows how to capture, inspect, and transform real images and video using a board that fits in your hand. The second edition updates the workflow for Python 3, modern Raspberry Pi OS, and OpenCV, making it a practical starting point for makers, students, and developers who want to build vision projects on affordable hardware.

What the Second Edition Covers

Ashwin Pajankar walks through the full path from a fresh Raspberry Pi to working computer vision code. Early chapters cover choosing a board, installing and configuring the operating system, connecting remotely over SSH, and setting up a comfortable development environment. From there, the book introduces Python 3, NumPy, Matplotlib, and GPIO programming before moving into OpenCV.

• Setting up Raspbian/Raspberry Pi OS and preparing the Pi for computer vision
• Remote access with SSH and remote desktop
• Python 3 essentials, NumPy arrays, Matplotlib plotting, and GPIO basics
• Working with images and video using OpenCV
• Capturing from USB webcams and the Raspberry Pi camera module
• Image properties, arithmetic operations, bitwise logic, and channel splitting
• Colorspaces, translation, rotation, affine and perspective transforms
• Thresholding, Otsu’s method, adaptive thresholding, noise, kernels, and 2D convolution filtering

From Camera to Code 👁️

One of the book’s strengths is that it connects hardware and software rather than leaving them in separate silos. You will see how a webcam or Pi camera feeds data into Python, how OpenCV represents that data, and how simple operations like scaling, blurring, and thresholding prepare images for more advanced work. The examples are aimed at readers who learn by doing, with code that can be run and modified on a Raspberry Pi.

Who This Book Is For

If you are comfortable with basic programming and want to explore computer vision on low-cost hardware, this book is a strong fit. It is also useful for hobbyists, students, and educators who want a structured introduction to OpenCV and Python 3 on the Raspberry Pi. Readers who already know Python will be able to move quickly through the language review and spend more time on the vision chapters.

Build a Foundation for Vision Projects

By the end, you will have a working understanding of how to set up a Raspberry Pi for vision work, acquire images and video, manipulate them with OpenCV, and apply common preprocessing techniques. That foundation can support projects such as motion detection, color tracking, image filtering, and camera-based experiments. For anyone curious about embedded computer vision, this second edition offers a clear, hands-on route into the subject.