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OpenCV 3.x with Python By Example

You're reading from   OpenCV 3.x with Python By Example Make the most of OpenCV and Python to build applications for object recognition and augmented reality

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788396905
Length 268 pages
Edition 2nd Edition
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Authors (2):
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Gabriel Garrido Calvo Gabriel Garrido Calvo
Author Profile Icon Gabriel Garrido Calvo
Gabriel Garrido Calvo
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Table of Contents (17) Chapters Close

Title Page
Copyright and Credits
Contributors
Packt Upsell
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. Seam Carving 7. Detecting Shapes and Segmenting an Image 8. Object Tracking 9. Object Recognition 10. Augmented Reality 11. Machine Learning by an Artificial Neural Network 1. Other Books You May Enjoy

What are integral images?


If we want to compute Haar features, we will have to compute the summations of many different rectangular regions within the image. If we want to effectively build the feature set, we need to compute these summations at multiple scales. This is a very expensive process! If we want to build a real-time system, we cannot spend so many cycles computing these sums. So we use something called integral images:

To compute the sum of any rectangle in the image, we don't need to go through all the elements in that rectangular area. Let's say AP indicates the sum of all the elements in the rectangle formed by the top-left point and the point P in the image as the two diagonally opposite corners. So now, if we want to compute the area of the rectangle ABCD, we can use the following formula:

Area of the rectangle ABCD = AC - (AB + AD - AA)

Why do we care about this particular formula? As we discussed earlier, extracting Haar features includes computing the areas of a large number...

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