Raspberry Pi Computer Vision Programming
Language: English
Published by Packt Publishing, 2020
- Softcover
- New
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Seller Inventory # L0-9781800207219
- Title
- Raspberry Pi Computer Vision Programming
- Author
- Ashwin Pajankar
- Publisher
- Packt Publishing
- Publication year
- 2020
- Condition
- New
- Binding
- PAP
- Language
- English
- ISBN 10
- 1800207212
- ISBN 13
- 9781800207219
- Edition
- 2nd Edition
- Item weight
- 655 grams
Perform a wide variety of computer vision tasks such as image processing and manipulation, feature and object detection, and image restoration to build real-life computer vision applications
Key Features
- Explore the potential of computer vision with Raspberry Pi and Python programming
- Perform computer vision tasks such as image processing and manipulation using OpenCV and Raspberry Pi
- Discover easy-to-follow examples and screenshots to implement popular computer vision techniques and applications
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
Who this book is for
This book is for beginners as well as experienced Raspberry Pi and Python 3 enthusiasts who are looking to explore the amazing world of computer vision. Working knowledge of the Python 3 programming language is assumed.
Table of Contents
- Introduction to Computer Vision and Raspberry Pi
- Prepare Raspberry Pi for Computer Vision
- Programming with Python 3, GPIO, NumPy, and Matplotlib
- Getting started with Computer Vision
- Basics of Image Processing
- Colorspaces, Transformations, and Thresholding
- Let's Make Some Noise
- High Pass Filters and Feature Detection
- Image Restoration, Quantization, and Depth Map
- Histograms, Contours, and Morphological Transformations
- Real-life Computer Vision Applications
- Wrapping Up with Mahotas and Jupyter Notebook
- Appendix
"Synopsis" may belong to another edition of this title.
About the Author
Ashwin Pajankar is a Polymath. He is a Science Popularizer, a Programmer, a Maker, an Author, and a Youtuber. He graduated from IIIT Hyderabad with MTech in Computer Science and Engineering. He has a keen interest in the promotion of Science, Technology, Engineering, and Mathematics (STEM) education.
"About the title" may belong to another edition of this title.
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