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Learn OpenCV 4 by Building Projects

Learn OpenCV 4 by Building Projects

By : Millán Escrivá, Vinícius G. Mendonça, Joshi
2.5 (2)
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Learn OpenCV 4 by Building Projects

Learn OpenCV 4 by Building Projects

2.5 (2)
By: Millán Escrivá, Vinícius G. Mendonça, Joshi

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. Whether you’re completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects – Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. You’ll begin with the installation of OpenCV and the basics of image processing. Then, you’ll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module. By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch.
Table of Contents (14 chapters)
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Creating the graphical user interface

Before we start with the image processing algorithms, we create the main user interface for our application. We are going to use the Qt-based user interface to allow us to create single buttons. The application receives one input parameter to load the image to process, and we are going to create four buttons, as follows:

  • Show histogram
  • Equalize histogram
  • Lomography effect
  • Cartoonize effect

We can see the four results in the following screenshot:

Let's begin developing our project. First of all, we are going to include the OpenCV – required headers, define an image matrix to store the input image, and create a constant string to use the new command-line parser already available from OpenCV 3.0; in this constant, we allow only two input parameters, help and the required image input:

// OpenCV includes 
#include "opencv2/core...

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