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  • Book Overview & Buying Learn OpenCV 4 by Building Projects
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Learn OpenCV 4 by Building Projects

Learn OpenCV 4 by Building Projects - Second Edition

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

Learn OpenCV 4 by Building Projects

2.5 (2)
By: David Millán Escrivá, Vinícius G. Mendonça, Prateek 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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Preprocessing the input image

This section introduces some of the most common techniques that we can apply for preprocessing images in the context of object segmentation/detection. The preprocessing is the first change we make to a new image before we start working and extracting the information we require from it. Normally, in the preprocessing step, we try to minimize the image noise, light conditions, or image deformation due to a camera lens. These steps minimize errors while detecting objects or segments in our image.

Noise removal

If we don't remove the noise, we can detect more objects than we expect because noise is normally represented as small points in the image and can be segmented as an object. The sensor...

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Learn OpenCV 4 by Building Projects
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