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OpenCV 3.x with Python By Example - Second Edition

You're reading from  OpenCV 3.x with Python By Example - Second Edition

Product type Book
Published in Jan 2018
Publisher Packt
ISBN-13 9781788396905
Pages 268 pages
Edition 2nd Edition
Languages
Authors (2):
Gabriel Garrido Calvo Gabriel Garrido Calvo
Profile icon Gabriel Garrido Calvo
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi
View More author details
Toc

Table of Contents (17) Chapters close

Title Page
Copyright and Credits
Contributors
Packt Upsell
Preface
1. Applying Geometric Transformations to Images 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

How to censor a shape?


Let's say you are dealing with images and you want to block out a particular shape. Now, you might say that you will use shape matching to identify the shape and then just block it out, right? But the problem here is that we don't have any template available. So, how do we go about doing this? Shape analysis comes in various forms, and we need to build our algorithm depending on the situation. Let's consider the following figure:

Let's say we want to identify all the boomerang shapes and then block them out without using any template images. As you can see, there are various other weird shapes in that image and the boomerang shapes are not really smooth. We need to identify the property that's going to differentiate the boomerang shape from the other shapes present. Let's consider the convex hull. If you take the ratio of the area of each shape to the area of the convex hull, we can see that this can be a distinguishing metric. This metric is called solidity factor...

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