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OpenCV 4 Computer Vision Application Programming Cookbook

You're reading from   OpenCV 4 Computer Vision Application Programming Cookbook Build complex computer vision applications with OpenCV and C++

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789340723
Length 494 pages
Edition 4th Edition
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Authors (2):
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Robert Laganiere Robert Laganiere
Author Profile Icon Robert Laganiere
Robert Laganiere
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
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Toc

Table of Contents (17) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating the Pixels 3. Processing Color Images with Classes 4. Counting the Pixels with Histograms 5. Transforming Images with Morphological Operations 6. Filtering the Images 7. Extracting Lines, Contours, and Components 8. Detecting Interest Points 9. Describing and Matching Interest Points 10. Estimating Projective Relations in Images 11. Reconstructing 3D Scenes 12. Processing Video Sequences 13. Tracking Visual Motion 14. Learning from Examples 15. OpenCV Advanced Features 16. Other Books You May Enjoy

Manipulating the Pixels

In order to build computer vision applications, you need to be able to access the image content and, eventually, modify or create images. This chapter will teach you how to manipulate the picture elements (also known as pixels). You will learn how to scan an image and process each of its pixels. You will also learn how to do this efficiently, since even images of modest dimensions can contain hundreds of thousands of pixels.

Fundamentally, an image is a matrix of numerical values. This is why, as we learned in Chapter 1, Playing with Images, OpenCV 4 manipulates them using the cv::Mat data structure. Each element of the matrix represents one pixel. For a gray-level image (a black-and-white image), pixels are unsigned 8-bit values where 0 corresponds to black and 255 corresponds to white. In the case of color images, three primary color values are required...

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