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Building Computer Vision Projects with OpenCV 4 and C++

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

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Product type Course
Published in Mar 2019
Publisher
ISBN-13 9781838644673
Length 538 pages
Edition 1st Edition
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Authors (4):
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Roy Shilkrot Roy Shilkrot
Author Profile Icon Roy Shilkrot
Roy Shilkrot
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
Vinícius G. Mendonça Vinícius G. Mendonça
Author Profile Icon Vinícius G. Mendonça
Vinícius G. Mendonça
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Table of Contents (28) Chapters Close

Title Page
Copyright and Credits
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 1. Other Books You May Enjoy Index

Chapter 1. Getting Started with OpenCV

Computer vision applications are interesting and useful, but the underlying algorithms are computationally intensive. With the advent of cloud computing, we are getting more processing power to work with.

The OpenCV library enables us to run computer vision algorithms efficiently in real time. It has been around for many years and has become the standard library in this field. One of the main advantages of OpenCV is that it is highly optimized and available on almost all platforms.

This book will cover the various algorithms we will be using, why we are using them, and how to implement them in OpenCV.

In this chapter, we are going to learn how to install OpenCV on various operating systems. We will discuss what OpenCV offers out of the box, and the various things that we can do using the inbuilt functions.

By the end of this chapter, you will be able to answer the following questions:

  • How do humans process visual data, and how do they understand image content?
  • What can we do with OpenCV, and what are the various modules available in OpenCV that can be used to achieve those things?
  • How do we install OpenCV on Windows, Linux, and Mac OS X?
You have been reading a chapter from
Building Computer Vision Projects with OpenCV 4 and C++
Published in: Mar 2019
Publisher:
ISBN-13: 9781838644673
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