Book Image

Raspberry Pi Computer Vision Programming - Second Edition

By : Ashwin Pajankar
5 (1)
Book Image

Raspberry Pi Computer Vision Programming - Second Edition

5 (1)
By: Ashwin Pajankar

Overview of this book

Raspberry Pi is one of the popular single-board computers of our generation. All the major image processing and computer vision algorithms and operations can be implemented easily with OpenCV on Raspberry Pi. This updated second edition is packed with cutting-edge examples and new topics, and covers the latest versions of key technologies such as Python 3, Raspberry Pi, and OpenCV. This book will equip you with the skills required to successfully design and implement your own OpenCV, Raspberry Pi, and Python-based computer vision projects. At the start, you'll learn the basics of Python 3, and the fundamentals of single-board computers and NumPy. Next, you'll discover how to install OpenCV 4 for Python 3 on Raspberry Pi, before covering major techniques and algorithms in image processing, manipulation, and computer vision. By working through the steps in each chapter, you'll understand essential OpenCV features. Later sections will take you through creating graphical user interface (GUI) apps with GPIO and OpenCV. You'll also learn to use the new computer vision library, Mahotas, to perform various image processing operations. Finally, you'll explore the Jupyter Notebook and how to set up a Windows computer and Ubuntu for computer vision. By the end of this book, you'll be able to confidently build and deploy computer vision apps.
Table of Contents (15 chapters)

Preface

Computer vision and image processing have extended from being a field of niche research to everyday usage. However, despite this revolution, one of the key challenges faced in computer vision development and application development is a lack of a well-designed guide that teaches you how it works step by step. This book addresses this key challenge.

We will start with the basics of Raspberry Pi and Python and explore Python 3 programming with various supporting libraries, such as NumPy, SciPy, and Matplotlib. Next, we will understand the basics of General-Purpose Input Output (GPIO) pins on Raspberry Pi and learn about its programming with Python 3. We will look at a lot of examples of Raspberry Pi and computer vision programming with Python and GPIO throughout the entirety of this book.

Then, we will move on to the installation of OpenCV on Raspberry Pi. We will look at the basics of OpenCV programming and explore the concepts of advanced image processing and computer vision. We will learn about and demonstrate concepts such as thresholding, segmentation, image quantization, image restoration, mathematical morphology, and contours. Then, we will implement a few real-life applications with OpenCV, Python, and GPIO.

We will also learn how to use another library—Mahotas—and the Jupyter Notebook. Additionally, we will learn how to install all the libraries that we will discuss on a Windows computer. Finally, the Appendix section has a range of useful topics relating to Raspberry Pi that are not included in other chapters.