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OpenCV 4 Computer Vision Application Programming Cookbook

You're reading from   OpenCV 4 Computer Vision Application Programming Cookbook Build complex computer vision applications with OpenCV and C++

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789340723
Length 494 pages
Edition 4th Edition
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Authors (2):
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Robert Laganiere Robert Laganiere
Author Profile Icon Robert Laganiere
Robert Laganiere
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
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Toc

Table of Contents (17) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating the Pixels 3. Processing Color Images with Classes 4. Counting the Pixels with Histograms 5. Transforming Images with Morphological Operations 6. Filtering the Images 7. Extracting Lines, Contours, and Components 8. Detecting Interest Points 9. Describing and Matching Interest Points 10. Estimating Projective Relations in Images 11. Reconstructing 3D Scenes 12. Processing Video Sequences 13. Tracking Visual Motion 14. Learning from Examples 15. OpenCV Advanced Features 16. Other Books You May Enjoy

Learning from Examples

Nowadays, machine learning is very often used to solve difficult machine vision problems. In fact, it is a rich field of research encompassing many important concepts that would deserve an entire cookbook by themselves. This chapter surveys some of the main machine learning techniques and explains how these can be deployed in computer vision systems using OpenCV.

At the core of machine learning is the development of computer systems that can learn, by themselves, how to react to data inputs. Instead of being explicitly programmed, machine learning systems automatically adapt and evolve when examples of desired behaviors are presented to them. Once a successful training phase is completed, it is expected that the trained system will output the correct response to new unseen queries.

Machine learning can solve many types of problems; however, our focus here...

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