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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

Summary

This chapter has shown several different types of image processing filters that can be used to generate various cartoon effects, from a plain sketch mode that looks like a pencil drawing, a paint mode that looks like a color painting, to a cartoon mode that overlays the sketch mode on top of the paint mode to appear like a cartoon. It also shows that other fun effects can be obtained, such as the evil mode, which greatly enhanced noisy edges and the alien mode, which changed the skin of a face to appear bright green.

There are many commercial smartphone apps that add similar fun effects on the user's face, such as cartoon filters and skin color changes. There are also professional tools using similar concepts, such as skin-smoothing video post-processing tools that attempt to beautify women's faces by smoothing their skin while keeping the edges and non-skin regions sharp, in order to make their faces appear younger.

This chapter shows how to port the application from a desktop to an embedded system by following the recommended guidelines of developing a working desktop version first, and then porting it to an embedded system and creating a user interface that is suitable for the embedded application. The image processing code is shared between the two projects so that the reader can modify the cartoon filters for the desktop application, and easily see those modifications in the embedded system as well.

Remember that this book includes an OpenCV installation script for Linux and full source code for all projects discussed.

In the next chapter, we are going to learn how to use multiple view stereo (MVS) and structure from motion (SfM) for 3D reconstruction, and how to export the final result in OpenMVG format.

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