Image Processing and Acquisition using Python

Ravishankar Chityala, Sridevi Pudipeddi

• Verlag: Chapman and Hall/CRC
• Jahr: 2014
• ISBN:
  9781498760577
• Auflage: 1
• Thema: Matematica
• Thema: Matematica generale

Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing-one of the first books to integrate these topics together. By improving readers' knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectiv

Part I

Introduction to Images and Computing using Python

Chapter 1

Introduction to Python

1.1 Introduction

Before we begin discussion on image acquisition and processing using Python, we will provide an overview of the various aspects of Python. This chapter focuses on some of the basic materials covered by many other books [2], [36], [54], [103]. If you are already familiar with Python and are currently using it then you can skip this chapter.

We begin with an introduction to Python. We discuss the installation of Python with all the modules. The details of the installation process are available in Appendix A. To simplify the installation, we will discuss the Python distributions Enthought Python Distribution (EPD) and PythonXY. If you are an advanced programmer, you can install the various modules like scipy, numpy, Python imaging library etc. in the basic Python distribution. Once the installation has been completed, we can begin exploring the various features of Python. We will quickly review the various data structures such as list, dictionary, and tuples and statements such as for-loop, if-else, iterators and list comprehension.

1.2 What is Python?

Python is a popular high-level programming language. It can handle various programming tasks such as numerical computation, web development, database programming, network programming, parallel processing, etc. Python is popular for various reasons including:

1. It is free.
2. It is available on all the popular operating systems such as Windows, Mac or Linux.
3. It is an interpreted language. Hence, programmers can test portions of code on the command line before incorporating it into their program. There is no need for compiling or linking.
4. It gives the ability to program faster.
5. It is syntactically simpler than C/C++/Fortran. Hence it is highly readable and easier to debug.
6. It comes with various modules that are standard or can be installed to an existing Python installation. These modules can perform various tasks like reading and writing various files, scientific computation, visualization of data etc.
7. Programs written i...

Inhaltsverzeichnis

• Preliminaries
• Series
• Dedication
• Foreword
• Preface
• Introduction
• About the Authors
• List of Symbols and Abbreviations
• Part I: Introduction to Images and Computing using Python
• Part II: Image Processing using Python
• Part III: Image Acquisition
• Appendix A: Installing Python Distributions
• Appendix B: Parallel Programming Using MPI4Py
• Appendix C: Introduction to ImageJ
• Appendix D: MATLAB® and Numpy Functions
• Bibliography