Book Image

Computer Vision with OpenCV 3 and Qt5

By : Amin Ahmadi Tazehkandi
4 (1)
Book Image

Computer Vision with OpenCV 3 and Qt5

4 (1)
By: Amin Ahmadi Tazehkandi

Overview of this book

Developers have been using OpenCV library to develop computer vision applications for a long time. However, they now need a more effective tool to get the job done and in a much better and modern way. Qt is one of the major frameworks available for this task at the moment. This book will teach you to develop applications with the combination of OpenCV 3 and Qt5, and how to create cross-platform computer vision applications. We’ll begin by introducing Qt, its IDE, and its SDK. Next you’ll learn how to use the OpenCV API to integrate both tools, and see how to configure Qt to use OpenCV. You’ll go on to build a full-fledged computer vision application throughout the book. Later, you’ll create a stunning UI application using the Qt widgets technology, where you’ll display the images after they are processed in an efficient way. At the end of the book, you’ll learn how to convert OpenCV Mat to Qt QImage. You’ll also see how to efficiently process images to filter them, transform them, detect or track objects as well as analyze video. You’ll become better at developing OpenCV applications.
Table of Contents (19 chapters)
Title Page
Dedication
Packt Upsell
Foreword
Contributors
Preface

Summary


Writing computer vision applications that perform real-time image processing is one of the hot topics of today, and OpenCV contains many classes and functions to help with simplifying the development of such applications. In this chapter, we tried to cover some of the most important classes and functions provided by OpenCV for real-time processing of videos and images. We learned about the MeanShift, CamShift, and background subtraction algorithms in OpenCV, which are packed into fast and efficient classes which are, at the same time, very easy to use, provided that you are familiar with the basic concepts used in most of them, such as histograms and back-projection images. That is why we started by learning all about histograms, how they are calculated, visualized, and compared with each other. We also learned how back-projection images are calculated and used as a lookup table to update images. We used the same also in the MeanShift/CamShift algorithms to track objects of specific...