Raspberry Pi Computer Vision Programming

Design and implement your own computer vision applications with the Raspberry Pi

Raspberry Pi Computer Vision Programming

Learning
Ashwin Pajankar

3 customer reviews
Design and implement your own computer vision applications with the Raspberry Pi
$19.99
$24.99
RRP $19.99
RRP $24.99
eBook
Print + eBook

Instantly access this course right now and get the skills you need in 2017

With unlimited access to a constantly growing library of over 4,000 eBooks and Videos, a subscription to Mapt gives you everything you need to get that next promotion or to land that dream job. Cancel anytime.

Free Sample

Book Details

ISBN 139781784398286
Paperback178 pages

Book Description

This book will provide you with the skills you need to successfully design and implement your own Raspberry Pi and Python-based computer vision projects.

From the beginning, this book will cover how to set up your Raspberry Pi for computer vision applications, exploring the basics of OpenCV, and how to design and implement real-life computer vision applications on your own. By sequentially working through the steps in each chapter, you will quickly be able to master the features of OpenCV. In the end of the book, you will also be introduced to SimpleCV, which is another powerful computer vision library for Python. Featuring plenty of coding examples and exercises, this book offers you an unparalleled learning experience.

Table of Contents

Chapter 1: Introduction to Computer Vision and Raspberry Pi
Computer vision
OpenCV
Single-board computers and the Raspberry Pi
Setting up your Raspberry Pi B+
Preparing your Pi for computer vision
NumPy
Summary
Chapter 2: Working with Images, Webcams, and GUI
Running Python programs with Raspberry Pi
Working with images
Drawing geometric shapes
Working with trackbar and named window
Working with a webcam
Working with a webcam using OpenCV
Working with the Pi camera module
Chapter 3: Basic Image Processing
Retrieving image properties
Arithmetic operations on images
Splitting and merging image colour channels
Exercise
Summary
Chapter 4: Colorspaces, Transformations, and Thresholds
Colorspaces and conversions
Tracking in real time based on color
Image transformations
Thresholding image
Exercise
Summary
Chapter 5: Let's Make Some Noise
Noise
Exercise
Summary
Chapter 6: Edges, Circles, and Lines' Detection
High-pass filters
Canny Edge detector
Hough circle and line transforms
Exercise
Summary
Chapter 7: Image Restoration, Quantization, and Depth Map
Restoring images using inpainting
Image segmentation
K-means clustering and image quantization
Disparity map and depth estimation
Summary
Chapter 8: Histograms, Contours, Morphological Transformations, and Performance Measurement
Image histograms
Image contours
Morphological transformations on image
OpenCV performance measurement and improvement
Summary
Chapter 9: Real-life Computer Vision Applications
Barcode detection
Motion detection and tracking
Hand gesture recognition
Chroma key with green screen
Summary
Chapter 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

What You Will Learn

  • Set up your Raspberry Pi and master computer vision with OpenCV
  • Work with images, videos, webcams, the Pi camera, and create amazing timelapse videos
  • Blend images and create artistic effects such as image transitioning
  • Transform images, change colorspaces, and track objects based on colors
  • Use various high- and low-pass filters to remove noise from the image
  • Find contours and segments in images and detect edges, lines, and circles
  • Install another simple yet powerful library, SimpleCV, and with its help create real-life applications

Authors

Table of Contents

Chapter 1: Introduction to Computer Vision and Raspberry Pi
Computer vision
OpenCV
Single-board computers and the Raspberry Pi
Setting up your Raspberry Pi B+
Preparing your Pi for computer vision
NumPy
Summary
Chapter 2: Working with Images, Webcams, and GUI
Running Python programs with Raspberry Pi
Working with images
Drawing geometric shapes
Working with trackbar and named window
Working with a webcam
Working with a webcam using OpenCV
Working with the Pi camera module
Chapter 3: Basic Image Processing
Retrieving image properties
Arithmetic operations on images
Splitting and merging image colour channels
Exercise
Summary
Chapter 4: Colorspaces, Transformations, and Thresholds
Colorspaces and conversions
Tracking in real time based on color
Image transformations
Thresholding image
Exercise
Summary
Chapter 5: Let's Make Some Noise
Noise
Exercise
Summary
Chapter 6: Edges, Circles, and Lines' Detection
High-pass filters
Canny Edge detector
Hough circle and line transforms
Exercise
Summary
Chapter 7: Image Restoration, Quantization, and Depth Map
Restoring images using inpainting
Image segmentation
K-means clustering and image quantization
Disparity map and depth estimation
Summary
Chapter 8: Histograms, Contours, Morphological Transformations, and Performance Measurement
Image histograms
Image contours
Morphological transformations on image
OpenCV performance measurement and improvement
Summary
Chapter 9: Real-life Computer Vision Applications
Barcode detection
Motion detection and tracking
Hand gesture recognition
Chroma key with green screen
Summary
Chapter 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

Book Details

ISBN 139781784398286
Paperback178 pages
Read More
From 3 reviews

Read More Reviews