Mastering OpenCV 4电子书

Title Page

Copyright and Credits

Mastering OpenCV 4 Third Edition

Dedication

About Packt

Why subscribe?

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Contributors

About the authors

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

Download the color images

Conventions used

Get in touch

Reviews

Cartoonifier and Skin Color Analysis on the RaspberryPi

Accessing the webcam

Main camera processing loop for a desktop app

Generating a black and white sketch

Generating a color painting and a cartoon

Generating an evil mode using edge filters

Generating an alien mode using skin detection

Skin detection algorithm

Showing the user where to put their face

Implementation of the skin color changer

Reducing the random pepper noise from the sketch image

Porting from desktop to an embedded device

Equipment setup to develop code for an embedded device

Configuring a new Raspberry Pi

Installing OpenCV on an embedded device

Using the Raspberry Pi Camera Module

Installing the Raspberry Pi Camera Module driver

Making Cartoonifier run in fullscreen

Hiding the mouse cursor

Running Cartoonifier automatically after bootup

Speed comparison of Cartoonifier on desktop versus embedded

Changing the camera and camera resolution

Power draw of Cartoonifier running on desktop versus embedded system

Streaming video from Raspberry Pi to a powerful computer

Customizing your embedded system!

Summary

Explore Structure from Motion with the SfM Module

Technical requirements

Core concepts of SfM

Calibrated cameras and epipolar geometry

Stereo reconstruction and SfM

Implementing SfM in OpenCV

Image feature matching

Finding feature tracks

3D reconstruction and visualization

MVS for dense reconstruction

Summary

Face Landmark and Pose with the Face Module

Technical requirements

Theory and context

Active appearance models and constrained local models

Regression methods

Facial landmark detection in OpenCV

Measuring error

Estimating face direction from landmarks

Estimated pose calculation

Projecting the pose on the image

Summary

Number Plate Recognition with Deep Convolutional Networks

Introduction to ANPR

ANPR algorithm

Plate detection

Segmentation

Classification

Plate recognition

OCR segmentation

Character classification using a convolutional neural network

Creating and training a convolutional neural network with TensorFlow

Preparing the data

Creating a TensorFlow model

Preparing a model for OpenCV

Import and use model in OpenCV C++ code

Summary

Face Detection and Recognition with the DNN Module

Introduction to face detection and face recognition

Face detection

Implementing face detection using OpenCV cascade classifiers

Loading a Haar or LBP detector for object or face detection

Accessing the webcam

Detecting an object using the Haar or LBP classifier

Detecting the face

Implementing face detection using the OpenCV deep learning module

Face preprocessing

Eye detection

Eye search regions

Geometrical transformation

Separate histogram equalization for left and right sides

Smoothing

Elliptical mask

Collecting faces and learning from them

Collecting preprocessed faces for training

Training the face recognition system from collected faces

Viewing the learned knowledge

Average face

Eigenvalues, Eigenfaces, and Fisherfaces

Face recognition

Face identification – recognizing people from their faces

Face verification—validating that it is the claimed person

Finishing touches—saving and loading files

Finishing touches—making a nice and interactive GUI

Drawing the GUI elements

Startup mode

Detection mode

Collection mode

Training mode

Recognition mode

Checking and handling mouse clicks

Summary

References

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

Threshold filter

Gaussian filter

Canny filter

Optical flow in your browser

Face detection using a Haar cascade classifier in your browser

Summary

Android Camera Calibration and AR Using the ArUco Module

Technical requirements

Augmented reality and pose estimation

Camera calibration

Augmented reality markers for planar reconstruction

Camera access in Android OS

Finding and opening the camera

Camera calibration with ArUco

Augmented reality with jMonkeyEngine

Summary

iOS Panoramas with the Stitching Module

Technical requirements

Panoramic image stitching methods

Feature extraction and robust matching for panoramas

Affine constraint

Random sample consensus (RANSAC)

Homography constraint

Bundle Adjustment

Warping images for panorama creation

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

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

Avoiding Common Pitfalls in OpenCV

History of OpenCV from v1 to v4

OpenCV and the data revolution in computer vision

Historic algorithms in OpenCV

How to check when an algorithm was added to OpenCV

Common pitfalls and suggested solutions

Summary

Further reading

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