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Practical Computer Vision

You're reading from   Practical Computer Vision Extract insightful information from images using TensorFlow, Keras, and OpenCV

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788297684
Length 234 pages
Edition 1st Edition
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Author (1):
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Abhinav Dadhich Abhinav Dadhich
Author Profile Icon Abhinav Dadhich
Abhinav Dadhich
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Table of Contents (12) Chapters Close

Preface 1. A Fast Introduction to Computer Vision FREE CHAPTER 2. Libraries, Development Platform, and Datasets 3. Image Filtering and Transformations in OpenCV 4. What is a Feature? 5. Convolutional Neural Networks 6. Feature-Based Object Detection 7. Segmentation and Tracking 8. 3D Computer Vision 9. Mathematics for Computer Vision 10. Machine Learning for Computer Vision 11. Other Books You May Enjoy

Summary

In this chapter, we saw a brief overview of computer vision with basic IO operations on images. Though it is a vast field, there are always exciting applications that can be built using computer vision techniques. This book tries to bridge the gap between theory and a practical approach to several of the popular algorithms. Further, in this book, we will begin with understanding more basic image operations that can perform filtering and transformations. Extending these basic techniques, we will then see what comprises of feature and how to compute them.

Following the introduction to computer vision in this chapter, we will start setting up libraries and an environment in the next chapter. These libraries will be used across the book. The datasets introduced in the next chapter can be the starting point for several algorithms further.

You have been reading a chapter from
Practical Computer Vision
Published in: Feb 2018
Publisher: Packt
ISBN-13: 9781788297684
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