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Mastering OpenCV 4

You're reading from   Mastering OpenCV 4 A comprehensive guide to building computer vision and image processing applications with C++

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Product type Paperback
Published in Dec 2018
Publisher
ISBN-13 9781789533576
Length 280 pages
Edition 3rd Edition
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Authors (2):
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Roy Shilkrot Roy Shilkrot
Author Profile Icon Roy Shilkrot
Roy Shilkrot
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
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Table of Contents (12) Chapters Close

Preface 1. Cartoonifier and Skin Color Analysis on the RaspberryPi 2. Explore Structure from Motion with the SfM Module FREE CHAPTER 3. Face Landmark and Pose with the Face Module 4. Number Plate Recognition with Deep Convolutional Networks 5. Face Detection and Recognition with the DNN Module 6. Introduction to Web Computer Vision with OpenCV.js 7. Android Camera Calibration and AR Using the ArUco Module 8. iOS Panoramas with the Stitching Module 9. Finding the Best OpenCV Algorithm for the Job 10. Avoiding Common Pitfalls in OpenCV 11. Other Books You May Enjoy

Historic algorithms in OpenCV

When starting to work on an OpenCV project, one should be aware of its historical past. OpenCV has existed for more than 15 years as an open source project, and despite its very dedicated management team that aims to better the library and keep it relevant, some implementations are more outdated than others. Some APIs are left for backward compatibility with previous versions, and others are targeted at specific algorithmic circumstances, all while newer algorithms are added.

Any engineer looking to choose the best performing algorithm for his work should have the tools to inquire about a specific algorithm to see when it was added and what are its origins (for example, a research paper). That is not to suggest that anything new is necessarily better, as some basic and older algorithms are excellent performers, and in most cases there's a clear...

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