Book Image

Computer Vision with Python 3

By : Saurabh Kapur
Book Image

Computer Vision with Python 3

By: Saurabh Kapur

Overview of this book

<p>This book is a thorough guide for developers who want to get started with building computer vision applications using Python 3. The book is divided into five sections: The Fundamentals of Image Processing, Applied Computer Vision, Making Applications Smarter,Extending your Capabilities using OpenCV, and Getting Hands on. Throughout this book, three image processing libraries Pillow, Scikit-Image, and OpenCV will be used to implement different computer vision algorithms.</p> <p>The book aims to equip readers to build Computer Vision applications that are capable of working in real-world scenarios effectively. Some of the applications that we will look at in the book are Optical Character Recognition, Object Tracking and building a Computer Vision as a Service platform that works over the internet.</p>
Table of Contents (17 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback
Introduction to Computer Vision using OpenCV

Chapter 1. Introduction to Image Processing

Before diving straight into image processing, let's understand images first. An image, as humans see it, is a two-dimensional grid with each cell in the grid filled with a color value, otherwise called a pixel value. Each cell of the grid is formally called a picture element (commonly abbreviated to pixel). A computer also sees the image in the same way. An image on a computer is a two-dimensional matrix of numbers with each cell in the matrix storing the corresponding pixel value(s) in the image. The following figure is an example of an image matrix. The matrix of the portion of the image in the red box is shown on the right:

Figure 1: This is the image matrix (right), as stored on a computer, of a small portion of the image (left) in the red box.

Image processing is the field of studying and analyzing images. There is a lot of hidden information in an image that we unconsciously process. For example, what are the different objects in the image?, Is there a car in the image? What are the similarities between any two images? Answers to these questions might feel simple to us humans, but for a computer, to answer such questions is extremely difficult. Through the course of this book, we aim to implement some of the algorithms that can help us answer some of these questions

The essence of image processing is to use the different properties of an image such as color, co-relations between different pixels, object placements, and other fine details to extract meaningful information such as edges, objects, and contours, which are formally called image features. These features can then be used in different applications such as medicine, security, social media services, and self-driving cars, some of which will be covered in the following chapters.