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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

Detecting corners in an image

When searching for interesting feature points in images, corners come out as an interesting solution. They are features that can be easily localized in an image and they should abound in scenes of man-made objects (where they are produced by walls, doors, windows, tables, and so on). Corners are also interesting because they are two-dimensional features that can be accurately localized (even at sub-pixel accuracy), as they are at the junction of two or more edges. This is in contrast to points located on a uniform area or on the contour of an object and points that would be difficult to repeatedly localize precisely on other images of the same object. The Harris feature detector is a classical approach to detect corners in an image. We will explore this operator in this recipe.

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