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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

Contour analysis and shape matching


Contour analysis is a very useful tool in the field of computer vision. We deal with a lot of shapes in the real world and contour analysis helps in analyzing those shapes using various algorithms. When we convert an image to grayscale and threshold it, we are left with a bunch of lines and contours. Once we understand the properties of different shapes, we will be able to extract detailed information from an image.

Let's say we want to identify the boomerang shape in the following image:

In order to do that, we first need to know what a regular boomerang looks like:

Now using the above image as a reference, can we identify what shape in our original image corresponds to a boomerang? If you notice, we cannot use a simple correlation based approach because the shapes are all distorted. This means that an approach where we look for an exact match won't work! We need to understand the properties of this shape and match the corresponding properties to identify...

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