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Raspberry Pi Computer Vision Programming. - Second Edition

You're reading from  Raspberry Pi Computer Vision Programming. - Second Edition

Product type Book
Published in Jun 2020
Publisher Packt
ISBN-13 9781800207219
Pages 306 pages
Edition 2nd Edition
Languages
Author (1):
Ashwin Pajankar Ashwin Pajankar
Profile icon Ashwin Pajankar

Table of Contents (15) Chapters

Preface 1. Chapter 1: Introduction to Computer Vision and the Raspberry Pi 2. Chapter 2: Preparing the Raspberry Pi for Computer Vision 3. Chapter 3: Introduction to Python Programming 4. Chapter 4: Getting Started with Computer Vision 5. Chapter 5: Basics of Image Processing 6. Chapter 6: Colorspaces, Transformations, and Thresholding 7. Chapter 7: Let's Make Some Noise 8. Chapter 8: High-Pass Filters and Feature Detection 9. Chapter 9: Image Restoration, Segmentation, and Depth Maps 10. Chapter 10: Histograms, Contours, and Morphological Transformations 11. Chapter 11: Real-Life Applications of Computer Vision 12. Chapter 12: Working with Mahotas and Jupyter 13. Chapter 13: Appendix 14. Other Books You May Enjoy

Chapter 11: Real-Life Applications of Computer Vision

In the previous chapter, we studied various advanced concepts in computer vision such as morphological operations and contours.

This chapter is the culmination of all the computer vision concepts we've learned and demonstrated in the earlier chapters. In this chapter, we will use the computer vision operation we learned about earlier in detail to implement a few real-life projects. We will also learn about a few new concepts such as background subtraction and the computation of optical flow and then demonstrate them for small applications. This chapter contains a lot of hands-on programming examples, as well as detailed explanations of the code and new functionality.

In this chapter, we will learn and demonstrate the code for the following topics:

  • Implementing the Max RGB filter
  • Implementing background subtraction
  • Computing the optical flow
  • Detecting and tracking motion
  • Detecting barcodes in images...
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