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You're reading from Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection

Product type Course

Published in Mar 2019

Publisher

ISBN-13 9781838644673

Length 538 pages

Edition 1st Edition

Languages

C++

Tools

OpenCV

Concepts

Computer Vision

Authors (4):

Roy Shilkrot

David Millán Escrivá

Vinícius G. Mendonça

Prateek Joshi

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Table of Contents (28) Chapters

Title Page

About Packt

Contributors

Preface

1. Getting Started with OpenCV FREE CHAPTER

2. An Introduction to the Basics of OpenCV

3. Learning Graphical User Interfaces

4. Delving into Histogram and Filters

5. Automated Optical Inspection, Object Segmentation, and Detection

6. Learning Object Classification

7. Detecting Face Parts and Overlaying Masks

8. Video Surveillance, Background Modeling, and Morphological Operations

9. Learning Object Tracking

10. Developing Segmentation Algorithms for Text Recognition

11. Text Recognition with Tesseract

12. Deep Learning with OpenCV

13. Cartoonifier and Skin Color Analysis on the RaspberryPi

14. Explore Structure from Motion with the SfM Module

15. Face Landmark and Pose with the Face Module

16. Number Plate Recognition with Deep Convolutional Networks

17. Face Detection and Recognition with the DNN Module

18. Android Camera Calibration and AR Using the ArUco Module

19. iOS Panoramas with the Stitching Module

20. Finding the Best OpenCV Algorithm for the Job

21. Avoiding Common Pitfalls in OpenCV

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Index

Chapter 2. An Introduction to the Basics of OpenCV

After covering OpenCV installation on different operating systems in Chapter 1, Getting Started with OpenCV, we are going to introduce the basics of OpenCV development in this chapter. It begins with showing how to create our project using CMake. We are going to introduce the basic image data structures and matrices, along with other structures that are required to work in our projects. We are going to introduce how to save our variables and data into files using the XML/YAML persistence OpenCV functions.

In this chapter, we will cover the following topics:

Configuring projects with CMake
Reading/writing images from/to disk
Reading videos and accessing camera devices
The main image structures (for example, matrices)
Other important and basic structures (for example, vectors and scalars)
An introduction to basic matrix operations
File storage operations with XML/YAML persistence OpenCV API

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You're reading from Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection

Table of Contents (28) Chapters

Chapter 2. An Introduction to the Basics of OpenCV

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Authors (4)

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