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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 scale-invariant features

The view invariance of feature detection was presented as an important concept in the introduction of this chapter. While orientation invariance, which is the ability to detect the same points even if an image is rotated, has been relatively well handled by the simple feature point detectors that have been presented so far, changes for invariance to scale are more difficult to achieve. To address this problem, the concept of scale-invariant features has been introduced in computer vision.

The idea here is to not only have a consistent detection of keypoints no matter at which scale an object is pictured, but to also have a scale factor associated with each of the detected feature points. Ideally, for the same object point featured at two different scales on two different images, the ratio of the two computed scale factors should correspond to...

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