Feature detection, description, and matching are probably some of the most important and hot topics in computer vision that are still in intensive progress and improvement. The algorithms that were presented in this chapter are but a fraction of the existing algorithms in the world, and the reason that we chose to present them is the fact that they are all more or less free to use by the public, and also the fact that they are included in OpenCV by default, under the feature2d module. If you are interested in learning about more algorithms, you can also check out Extra 2D Features Framework (xfeature2d), which contains non-free algorithms such as SURF and SIFT, or other algorithms still in experimental states. Of course, you need to separately download and add them to the OpenCV source code before building them to include their functions in your OpenCV installation. It is also recommended. However, also make sure to try out the algorithms you learned about in this chapter using different...
Computer Vision with OpenCV 3 and Qt5
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Computer Vision with OpenCV 3 and Qt5
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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.
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Current Title:
Computer Vision with OpenCV 3 and Qt5
Table of Contents (19 chapters)
Title Page
Dedication
Packt Upsell
Foreword
Contributors
Preface
Free Chapter
Introduction to OpenCV and Qt
Creating Our First Qt and OpenCV Project
Creating a Comprehensive Qt+OpenCV Project
Mat and QImage
The Graphics View Framework
Image Processing in OpenCV
Features and Descriptors
Multithreading
Video Analysis
Debugging and Testing
Linking and Deployment
Qt Quick Applications
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Customer Reviews