Book Description

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.

What you will learn

Set up a Raspberry Pi for computer vision applications
Perform basic image processing with libraries such as NumPy, Matplotlib, and OpenCV
Demonstrate arithmetical, logical, and other operations on images
Work with a USB webcam and the Raspberry Pi Camera Module
Implement low-pass and high-pass filters and understand their applications in image processing
Cover advanced techniques such as histogram equalization and morphological transformations
Create GUI apps with Python 3 and OpenCV
Perform machine learning with K-means clustering and image quantization