Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Applied Deep Learning and Computer Vision for Self-Driving Cars

You're reading from   Applied Deep Learning and Computer Vision for Self-Driving Cars Build autonomous vehicles using deep neural networks and behavior-cloning techniques

Arrow left icon
Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781838646301
Length 332 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Dr. S. Senthamilarasu Dr. S. Senthamilarasu
Author Profile Icon Dr. S. Senthamilarasu
Dr. S. Senthamilarasu
Balu Nair Balu Nair
Author Profile Icon Balu Nair
Balu Nair
Sumit Ranjan Sumit Ranjan
Author Profile Icon Sumit Ranjan
Sumit Ranjan
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Preface 1. Section 1: Deep Learning Foundation and SDC Basics
2. The Foundation of Self-Driving Cars FREE CHAPTER 3. Dive Deep into Deep Neural Networks 4. Implementing a Deep Learning Model Using Keras 5. Section 2: Deep Learning and Computer Vision Techniques for SDC
6. Computer Vision for Self-Driving Cars 7. Finding Road Markings Using OpenCV 8. Improving the Image Classifier with CNN 9. Road Sign Detection Using Deep Learning 10. Section 3: Semantic Segmentation for Self-Driving Cars
11. The Principles and Foundations of Semantic Segmentation 12. Implementing Semantic Segmentation 13. Section 4: Advanced Implementations
14. Behavioral Cloning Using Deep Learning 15. Vehicle Detection Using OpenCV and Deep Learning 16. Next Steps 17. Other Books You May Enjoy
Finding Road Markings Using OpenCV

In this chapter, we will use the concepts from Chapter 4, Computer Vision for Self-Driving Cars, to design a pipeline to identify road markings for self-driving cars using the OpenCV library. In general, we will preprocess our data with the OpenCV library and then feed in a deep learning network.

The main purpose of this chapter is to build a program that can identify road markings in a picture or a video. When we drive a car, we can see where the road markings are. A car obviously doesn't have any eyes, which is where computer vision comes in. In this chapter, we will use a complex algorithm that helps the computer see the world as we do. We will be using a series of camera images to identify road markings.

In this chapter, we will cover the following topics:

  • Finding road markings in an image
  • Detecting road markings in a video
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image