Python 3 Image Processing

Learn Image Processing with Python 3, NumPy, Matplotlib, and Scikit-image

Ashwin Pajankar

• Publisher: BPB Publications
• Year: 2019
• ISBN:
  9789388511728
• Topic: Computer Science
• Subtopic: Programming in Python
• Index: Computer Science

Gain a working knowledge of practical image processing and with scikit-image. Key Features

• Comprehensive coverage of various aspects of scientific Python and concepts in image processing.
• Covers various additional topics such as Raspberry Pi, conda package manager, and Anaconda distribution of Python.
• Simple language, crystal clear approach, and straight forward comprehensible presentation of concepts followed by code examples and output screenshots.
• Adopting user-friendly style for explanation of code examples.

Description
The book has been written in such a way that the concepts are explained in detail, giving adequate emphasis on code examples. To make the topics more comprehensive, screenshots and code samples are furnished extensively throughout the book. The book is conceptualized and written in such a way that the beginner readers will find it very easy to understand the concepts and implement the programs.
The book also features the most current version of Raspberry Pi and associated software with it. This book teaches novice beginners how to write interesting image processing programs with scientific Python ecosystem. The book will also be helpful to experienced professionals to make transition to rewarding careers in scientific Python and computer vision. What Will You Learn

• Raspberry Pi, Python 3 Basics
• Scientific Python Ecosystem
• NumPy and Matplotlib
• Visualization with Matplotlib
• Basic NumPy, Advanced Image Processing with NumPy and Matplotlib
• Getting started with scikit-image
• Thresholding, Histogram Equalization, and Transformations
• Kernels, Convolution, and Filters
• Morphological Operations and Image Restoration
• Noise Removal and Edge Detection
• Advanced Image Processing Operations

Who This Book Is For

• Students pursuing BE/BSc/ME/MSc/BTech/MTech in Computer Science, Electronics, Electrical, and Mathematics
• Python enthusiasts
• Computer Vision and Image Processing professionals
• Anyone fond of tinkering with Raspberry Pi
• Researchers in Computer Vision
• 
  Table of Contents
• Concepts in Image Processing
• Installing Python 3 on Windows
• Introduction to Raspberry Pi
• Python 3 Basics
• Introduction to the Scientific Python Ecosystem
• Introduction to NumPy and Matplotlib
• Visualization with Matplotlib
• Basic Image Processing with NumPy and Matplotlib
• Advanced Image Processing with NumPy and Matplotlib
• Getting Started with Scikit-Image
• Thresholding Histogram Equalization and Transformations
• Kernels, Convolution and Filters
• Morphological Operations and Image Restoration
• Noise Removal and Edge Detection
• Advanced Image Processing Operations
• Wrapping Up
• 
  About the Author
  ASHWIN PAJANKAR is a polymath. He has more than two decades of programming experience. He is a Science Popularizer, a Programmer, a Maker, an Author, and a Youtuber. He is passionate about STEM.
  (Science-Technology-Education-Mathematics) education. He is also a freelance software developer and technology trainer. He graduated from IIIT Hyderabad with M.Tech. in Computer Science and Engineering. He has worked in a few multinational corporations including Cisco Systems and Cognizant for more than a decade. His LinkedIn Profile: https://www.linkedin.com/in/ashwinpajankar/
  

Chapter 1

Concepts in Image Processing

I hope that you have read the preface and the table of contents thoroughly. If not, I recommend you to read them so that you will have an idea of the things that you can expect in this chapter and in the entire book. This being the first chapter of the book, is mostly an informative chapter and we will be learning a lot of important concepts for the topics we will see in this book. The programming hands on and other things will be there in the subsequent chapters. So, let us start the exciting journey of image processing by learning few important concepts.

1.1 Signal and Signal Processing

A fluctuating quantity that conveys information is known as a Signal. This is the scientific definition of signal. In our day to day life, we come across various types of signals like human gestures and TV/radio signals. All these signals convey some type of information to the recipients. Essentially, signals represent information.

Signal Processing is a scientific discipline that includes analysis of signals and extracting useful information from signals. Signal processing is a sub-discipline of Mathematics, Information Systems, and Electrical Engineering. The following Venn diagram shows us the relationship between all the disciplines mentioned above. (figure 1.1)

The system or the entity that carries out the task of processing signals is a Signal Processing System. The most prominent example of a signal processing system is a radio set that converts radio signals into audible signals. I prefer to classify the signal processing systems into naturally occurring signal processing systems (for example eyes) and man-made signal processing systems (like TV or radio). A man-made signal processing system that is made of electronic components is known as Electronic Signal Processing System. It is further classified into two types based on the nature of signals it processes, and electronic signal processing system can either be analog or digital.

Figure 1.1 Venn diagram for Signal Processing

We know that the analog signals are continuous and digital signals are discrete in nature. There are many more differences to the analog signals and digital signals. It is an interesting exercise to find out the difference between them.

1.2 Images and Image Processing

An image is a signal. The entity that processes images is an Image Processing System. It can be a natural system like eye and brain pair or man-made system. We can further classify man-made image processing systems into analog image processing systems and digital image processing systems.

A film camera or a motion picture camera is an analog image processing system where the picture is stored in the film which is an analog format. A film projector is also an example of an analog signal processing system. A digital camera and a computer are good examples of digital image processing systems. In the digital image processing, the images are captured and processed in the digital format. Digital image storage formats use digital bits (0s and 1s) to represent images. The digital images are stored in the digital storage mediums like optical storage (CD, DVD), semiconductor storage (SSD), or magnetic storage (tapes).

Image processing has applications in the following areas:

• Image sharpening and restoration
• Medical image processing
• Remote sensing
• Transmission and encoding of information
• Machine and Robot vision
• Pattern recognition and artificial intelligence
• Video processing
• Astronomy
• Computer graphics
• Spectroscopy

1.3 Summary

In this very short chapter, we have learned a few important concepts that we are going to see in details in the subsequent chapters of the book. In the next chapter, we will see the process of installation of Python 3 on the windows.

Exercise

As an exercise to this chapter, you can find out the more differences between analog and digital signals.

Chapter 2

Installing Python 3 on Windows

In the last chapter, we had a brief overview of the definitions of the important concepts that we will be discussing in this book. This chapter is dedicated to understanding the installation process of Python 3 on Windows computer and setting up the environment for programming.

2.1 Python Website

We can visit Python website to download the installable for Windows platform. The URL to the Python website is www.python.org. Open any web browser of your choice and visit this URL. The following page will appear in the browser windows: (figure 2.1)

Figure 2.1 Python Homepage

The page shown above in figure 2.1, is Python’s homepage. There is a Downloads link in the horizontal menu. Hover the mouse pointer over the Downloads link and following popup will appear: (figure 2.2)

Figure 2.2 Download for Windows

Based on your operating system, it will show you the appropriate download option. For Windows, it will be an executable installation file. At the time of writing this book, the most recent version is 3.7.3 and by the time you are reading this, it might have had new release already. But the concepts and programming examples in this book will mostly be the same. So, go ahead and download the file. Once the download finishes, you can find the python-3.7.3.exe in Downloads directory of your user. Once located, double click on it, to start installation process. Following window will appear: (figure 2.3)

Figure 2.3 Python 3 installation

Make sure to check all the checkboxes. The last checkbox will make sure that we can launch the Python 3 executable from the command prompt. Then, click Install Now. It will ask you for admin privileges. After that it will continue the installation process and once the installation is successful, it will show the following window, (figure 2.4)

Figure 2.4: Python 3 installation success

You can ...

Table of contents

• Cover
• Python 3 Image Processing
• Copyright
• Dedication
• Preface
• Acknowledgement
• About the Author
• Table of Content
• Chapter 1 : Concepts in Image Processing
• Chapter 2 : Installing Python 3 on Windows
• Chapter 3 : Introduction to Raspberry Pi
• Chapter 4 : Python 3 Basics
• Chapter 5 : Introduction to the Scientific Python Ecosystem
• Chapter 6 : Introduction to NumPy and Matplotlib
• Chapter 7 : Visualization with Matplotlib
• Chapter 8 : Basic Image Processing with NumPy and Matplotlib
• Chapter 9 : Advanced Image Processing with NumPy and Matplotlib
• Chapter 10 : Getting Started with Scikit-Image
• Chapter 11 : Thresholding Histogram Equalization and Transformations
• Chapter 12 : Kernels, Convolution and Filters
• Chapter 13 : Morphological Operations and Image Restoration
• Chapter 14 : Noise Removal and Edge Detection
• Chapter 15 : Advanced Image Processing Operations
• Chapter 16 : Wrapping Up