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Hands-On Computer Vision with Julia

You're reading from   Hands-On Computer Vision with Julia Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788998796
Length 202 pages
Edition 1st Edition
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Author (1):
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Dmitrijs Cudihins Dmitrijs Cudihins
Author Profile Icon Dmitrijs Cudihins
Dmitrijs Cudihins
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Table of Contents (11) Chapters Close

Preface 1. Getting Started with JuliaImages FREE CHAPTER 2. Image Enhancement 3. Image Adjustment 4. Image Segmentation 5. Image Representation 6. Introduction to Neural Networks 7. Using Pre-Trained Neural Networks 8. OpenCV 9. Assessments
10. Other Books You May Enjoy

ORB, rotation invariant image matching

The ORB descriptor is an improved version of BRIEF; it is a mix of a FAST keypoint detector combined with a modified and enhanced version of BRIEF.

A huge benefit of using ORB over BRIEF is the use of the harris corner measure that is built into ORB. It gives an opportunity to select top N uncorrelated keypoints. On top of that, the descriptor itself is enhanced and is rotation invariant.

We not only explore ORB by using a similar example, as in the previous section, but also apply rotation to the second image. We also use the CoordinateTransformations package to rotate the image around the center, as shown in the following code:

using Images, ImageFeatures, CoordinateTransformations

img1 = Gray.(load("sample-images/cat-3417184_640.jpg"))
img2 = Gray.(load("sample-images/cat-3417184_640_watermarked.jpg"))

Since the images...

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