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Raspberry Pi Computer Vision Programming
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Raspberry Pi Computer Vision Programming
by Ashwin Pajankar
Raspberry Pi Computer Vision Programming
Raspberry Pi Computer Vision Programming
Table of Contents
Raspberry Pi Computer Vision Programming
Credits
About the Author
About the Reviewers
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Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
1. Introduction to Computer Vision and Raspberry Pi
Computer vision
OpenCV
Single-board computers and the Raspberry Pi
Raspberry Pi
Operating systems
Raspbian
Setting up your Raspberry Pi B+
Preparing your microSD card manually
Booting up your Raspberry Pi for the first time
Shutting down and rebooting your Pi safely
Preparing your Pi for computer vision
Testing OpenCV installation with Python
NumPy
Array creation
Basic operations on arrays
Linear algebra
Summary
2. Working with Images, Webcams, and GUI
Running Python programs with Raspberry Pi
Working with images
Using matplotlib
Drawing geometric shapes
Working with trackbar and named window
Working with a webcam
Creating a timelapse sequence using fswebcam
Webcam video recording and playback
Working with a webcam using OpenCV
Saving a video and playback of a video using OpenCV
Working with the Pi camera module
Using raspistill and raspivid
Using picamera in Python with the Pi camera module
picamera and OpenCV
Summary
3. Basic Image Processing
Retrieving image properties
Arithmetic operations on images
Blending and transitioning images
Splitting and merging image colour channels
Creating a negative of an image
Logical operations on images
Exercise
Summary
4. Colorspaces, Transformations, and Thresholds
Colorspaces and conversions
Tracking in real time based on color
Image transformations
Scaling
Translation, rotation, and affine transformation
Perspective transformation
Thresholding image
Otsu's method
Exercise
Summary
5. Let's Make Some Noise
Noise
Introducing noise to an image
Kernels
2D convolution filtering
Low-pass filtering
Exercise
Summary
6. Edges, Circles, and Lines' Detection
High-pass filters
Canny Edge detector
Hough circle and line transforms
Exercise
Summary
7. Image Restoration, Quantization, and Depth Map
Restoring images using inpainting
Image segmentation
Mean shift algorithm based segmentation
K-means clustering and image quantization
Comparison of mean shift and k-means
Disparity map and depth estimation
Summary
8. Histograms, Contours, Morphological Transformations, and Performance Measurement
Image histograms
Image contours
Morphological transformations on image
OpenCV performance measurement and improvement
Summary
9. Real-life Computer Vision Applications
Barcode detection
Motion detection and tracking
Hand gesture recognition
Chroma key with green screen
Summary
10. Introduction to SimpleCV
SimpleCV and its installation on Raspberry Pi
Getting started with the camera, display, and images
Binary thresholding and color distances
The blur effect on a live web camera feed
Histogram calculation
Greyscale conversion
Detecting corners and lines in an image
Blob detection in images
Sending Raspberry Pi on a boating vacation
Exercise
Summary
Index
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