Book Image

Mastering OpenCV 4 - Third Edition

By : Roy Shilkrot, David Millán Escrivá
Book Image

Mastering OpenCV 4 - Third Edition

By: Roy Shilkrot, David Millán Escrivá

Overview of this book

Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You’ll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You’ll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You’ll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4.

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Table of Contents (12 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Cartoonifier and Skin Color Analysis on the RaspberryPi
Cartoonifier and Skin Color Analysis on the RaspberryPi
Accessing the webcam
Main camera processing loop for a desktop app
Implementation of the skin color changer
Porting from desktop to an embedded device
Summary
2
Explore Structure from Motion with the SfM Module
Explore Structure from Motion with the SfM Module
Technical requirements
Core concepts of SfM
Implementing SfM in OpenCV
Summary
3
Face Landmark and Pose with the Face Module
Face Landmark and Pose with the Face Module
Technical requirements
Theory and context
Facial landmark detection in OpenCV
Estimating face direction from landmarks
Summary
4
Number Plate Recognition with Deep Convolutional Networks
Number Plate Recognition with Deep Convolutional Networks
Introduction to ANPR
ANPR algorithm
Plate detection
Plate recognition
Summary
5
Face Detection and Recognition with the DNN Module
Face Detection and Recognition with the DNN Module
Introduction to face detection and face recognition
Summary
References
6
Introduction to Web Computer Vision with OpenCV.js
Introduction to Web Computer Vision with OpenCV.js
What is OpenCV.js?
Compile OpenCV.js
Basic introduction to OpenCV.js development
Accessing webcam streams
Image processing and basic user interface
Optical flow in your browser
Face detection using a Haar cascade classifier in your browser
Summary
7
Android Camera Calibration and AR Using the ArUco Module
Android Camera Calibration and AR Using the ArUco Module
Technical requirements
Augmented reality and pose estimation
Camera access in Android OS
Camera calibration with ArUco
Augmented reality with jMonkeyEngine
Summary
8
iOS Panoramas with the Stitching Module
iOS Panoramas with the Stitching Module
Technical requirements
Panoramic image stitching methods
Project overview
Setting up an iOS OpenCV project with CocoaPods
iOS UI for panorama capture
OpenCV stitching in an Objective-C++ wrapper
Summary
Further reading
9
Finding the Best OpenCV Algorithm for the Job
Finding the Best OpenCV Algorithm for the Job
Technical requirements
Is it covered in OpenCV?
Algorithm options in OpenCV
Which algorithm is best?
Example comparative performance test of algorithms
Summary
10
Avoiding Common Pitfalls in OpenCV
Avoiding Common Pitfalls in OpenCV
History of OpenCV from v1 to v4
Historic algorithms in OpenCV
Common pitfalls and suggested solutions
Summary
Further reading
11
Other Books You May Enjoy
Other Books You May Enjoy
Leave a review - let other readers know what you think

Technical requirements

The following technologies and installations are required to recreate the contents of this chapter:

  • macOSX machine (for example, MacBook, iMac) running macOS High Sierra v10.13+
  • iPhone 6+ running iOS v11+
  • Xcode v9+
  • CocoaPods v1.5+: https://cocoapods.org/
  • OpenCV v4.0 installed via CocoaPods

Build instructions for the preceding components, as well as the code to implement the concepts presented in this chapter, will be provided in the accompanying code repository.

The code for this chapter can be accessed via GitHub: https://github.com/PacktPublishing/Mastering-OpenCV-4-Third-Edition/tree/master/Chapter_08.

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