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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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Toc

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 is image segmentation?


Image segmentation is the process of separating an image into its constituent parts. It is an important step in many computer vision applications in the real world. There are many different ways of segmenting an image. When we segment an image, we separate the regions based on various metrics, such as color, texture, location, and so on. All the pixels within each region have something in common, depending on the metric we are using. Let's take a look at some of the popular approaches here.

To start with, we will be looking at a technique called GrabCut. It is an image segmentation method based on a more generic approach called graph-cuts. In the graph-cuts method, we consider the entire image to be a graph, and then we segment the graph based on the strength of the edges in that graph. We construct the graph by considering each pixel to be a node, and edges are constructed between the nodes, where edge weight is a function of the pixel values of those two nodes...

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