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)

Chapter 6: Colorspaces, Transformations, and Thresholding

In the previous chapter, we learned how to perform basic mathematical and logical operations on images. In this chapter, we will continue to explore some more intriguing concepts in the area of computer vision and its applications in the real world. Just like in the earlier chapters of this book, we will have a lot of hands-on exercises with Python 3 and create many real-world apps. We will cover a very wide variety of advanced topics in the area of computer vision. The major topics we will learn about are related to colorspaces, transformations, and thresholding images. After completing this chapter, you will be able to write programs for a few basic real-world applications, such as tracking an object that's a specific color. You will also be able to apply geometric and perspective transformations to images and live USB webcam feeds.

In this chapter, we will explore the following topics:

  • Colorspaces and converting...