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OpenCV with Python By Example

You're reading from   OpenCV with Python By Example Build real-world computer vision applications and develop cool demos using OpenCV for Python

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Product type Paperback
Published in Sep 2015
Publisher Packt
ISBN-13 9781785283932
Length 296 pages
Edition 1st Edition
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Author (1):
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Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (14) Chapters Close

Preface 1. Applying Geometric Transformations to Images FREE CHAPTER 2. Detecting Edges and Applying Image Filters 3. Cartoonizing an Image 4. Detecting and Tracking Different Body Parts 5. Extracting Features from an Image 6. Creating a Panoramic Image 7. Seam Carving 8. Detecting Shapes and Segmenting an Image 9. Object Tracking 10. Object Recognition 11. Stereo Vision and 3D Reconstruction 12. Augmented Reality Index

What are keypoints?

Now that we know that keypoints refer to the interesting regions in the image, let's dig a little deeper. What are keypoints made of? Where are these points? When we say "interesting", it means that something is happening in that region. If the region is just uniform, then it's not very interesting. For example, corners are interesting because there is sharp change in intensity in two different directions. Each corner is a unique point where two edges meet. If you look at the preceding images, you will see that the interesting regions are not completely made up of "interesting" content. If you look closely, we can still see plain regions within busy regions. For example, consider the following image:

What are keypoints?

If you look at the preceding object, the interior parts of the interesting regions are "uninteresting".

What are keypoints?

So, if we were to characterize this object, we would need to make sure that we picked the interesting points. Now, how do we define...

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