Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By : David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot
Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By: David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot

Overview of this book

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: •Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá •Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi
Table of Contents (28 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Chapter 4. Delving into Histogram and Filters

In the last chapter, we learned the basics of user interfaces in OpenCV, using Qt libraries or native ones; we also learned how to use advanced OpenGL user interfaces. We learned about basic color conversions, and filters that allow us to create our first application. This chapter will introduce you to the following concepts:

  • Histogram and histogram equalization
  • Look-up tables
  • Blur and median blur
  • Canny filter
  • Image-color equalization
  • Understanding the conversion between image types

After we learn the basics of OpenCV and user interfaces, we are going to create our first complete application in this chapter, a basic photo tool, and cover the following topics:

  • Generating a CMake script file
  • Creating the graphical user interface
  • Calculating and drawing a histogram
  • Histogram equalization
  • The lomography camera effect
  • The cartoonize effect

This application will help us to understand how to create an entire project from scratch and understand the histogram concept...