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Hands-On Vision and Behavior for Self-Driving Cars

You're reading from   Hands-On Vision and Behavior for Self-Driving Cars Explore visual perception, lane detection, and object classification with Python 3 and OpenCV 4

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Product type Paperback
Published in Oct 2020
Publisher Packt
ISBN-13 9781800203587
Length 374 pages
Edition 1st Edition
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Authors (2):
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Krishtof Korda Krishtof Korda
Author Profile Icon Krishtof Korda
Krishtof Korda
Luca Venturi Luca Venturi
Author Profile Icon Luca Venturi
Luca Venturi
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: OpenCV and Sensors and Signals
2. Chapter 1: OpenCV Basics and Camera Calibration FREE CHAPTER 3. Chapter 2: Understanding and Working with Signals 4. Chapter 3: Lane Detection 5. Section 2: Improving How the Self-Driving Car Works with Deep Learning and Neural Networks
6. Chapter 4: Deep Learning with Neural Networks 7. Chapter 5: Deep Learning Workflow 8. Chapter 6: Improving Your Neural Network 9. Chapter 7: Detecting Pedestrians and Traffic Lights 10. Chapter 8: Behavioral Cloning 11. Chapter 9: Semantic Segmentation 12. Section 3: Mapping and Controls
13. Chapter 10: Steering, Throttle, and Brake Control 14. Chapter 11: Mapping Our Environments 15. Assessments 16. Other Books You May Enjoy

Chapter 3: Lane Detection

This chapter will show one of the incredible things possible using computer vision in general and OpenCV in particular: lane detection. You will learn how to analyze an image and build more and more visual knowledge about it, one step after another, applying several filtering techniques, replacing noise and approximation with a better understanding of the image, until you will be able to detect where the lanes are on a straight road or on a turn, and we will apply this pipeline to a video to highlight the road.

You will see that this method relies on several assumptions that might not be true in the real world, though it can be adjusted to correct for that. Hopefully, you will find this chapter quite interesting.

We will cover the following topics:

  • Detecting lanes in a road
  • Color spaces
  • Perspective correction
  • Edge detection
  • Thresholding
  • Histograms
  • The sliding window algorithm
  • Polynomial fitting
  • Video filtering
  • ...
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