更新时间：2021-04-09 23:23:28
coverpage
Raspberry Pi Computer Vision Programming Second Edition
Why subscribe?
Contributors
About the author
About the reviewers
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Code in Action
Download the color images
Conventions used
Get in touch
Reviews
Chapter 1: Introduction to Computer Vision and the Raspberry Pi
Understanding computer vision
Single-board computers
Raspberry Pi
OSes for Raspberry Pi
Setting up Raspbian on a Raspberry Pi
Updating the RPi
Summary
Chapter 2: Preparing the Raspberry Pi for Computer Vision
Remotely logging into the RPi with SSH
Remote desktop access
Installing OpenCV on an RPi board
Heatsinks and overclocking RPi 4B
Chapter 3: Introduction to Python Programming
Technical requirements
Understanding Python 3
The SciPy ecosystem
RPi GPIO programming with Python 3
Chapter 4: Getting Started with Computer Vision
Exploring image datasets
Working with images using OpenCV
Using matplotlib to visualize images
Drawing geometric shapes with OpenCV and NumPy
Working with a GUI
Event handling and a primitive paint application
Working with a USB webcam
The Pi camera module
Chapter 5: Basics of Image Processing
Retrieving image properties
Basic operations on images
Arithmetic operations on images
Blending and transitioning images
Multiplying images by a constant and one another
Creating a negative of an image
Bitwise logical operations on images
Chapter 6: Colorspaces Transformations and Thresholding
Colorspaces and converting them
Performing transformation operations on images
Perspective transformation of images
Thresholding images
Chapter 7: Let's Make Some Noise
Noise
Working with kernels
2D convolution with the signal processing module in SciPy
Filtering and blurring with OpenCV
Chapter 8: High-Pass Filters and Feature Detection
Exploring high-pass filters
Working with the Canny edge detector
Harris corner detection
Exercise
Chapter 9: Image Restoration Segmentation and Depth Maps
Restoring damaged images using inpainting
Segmenting images
Disparity maps and depth estimation
Chapter 10: Histograms Contours and Morphological Transformations
Computing and visualizing histograms
Visualizing image contours
Applying morphological transformations to images
Chapter 11: Real-Life Applications of Computer Vision
Implementing the Max RGB filter
Implementing background subtraction
Computing the optical flow
Detecting and tracking motion
Detecting barcodes in images
Implementing the chroma key effect
