Image Processing with Python
Description
Scientists routinely use MATLAB or Octave for computational applications, and C/C++ or Fortran is still used for more rigorous modeling. However, Python is gaining popularity in scientific computing, as it has built-in scientific support through packages and toolkits such as SciPy and NumPy. It is open-source and has strong community support for developing packages and sharing expertise. Given this, it is inevitable that Python has become one of the most popular, flexible programming languages used today, and it is finding applications in science and engineering for everything from basic scripting to machine learning, and image processing is not immune to the march of Python.
This book explores the domain of image processing using Python with the help of working examples and accompanying code. Aimed at researchers and advanced students with a knowledge of image processing fundamentals, this book introduces Python programming via image processing and provides numerous hands-on examples and code snippets. The book will enable readers to appreciate the power of Python in this field, write their own code, and implement complex image processing algorithms such as image enhancement, compression, restoration, segmentation, watermarking, and encryption, and be able to incorporate machine learning models using relevant Python libraries.
This book is prepared to meet the needs of young researchers and professionals who are about to start their research journey in the domain of image processing. This book will help readers develop their own applications, whether for software-based implementation or simulation and testing before a final hardware implementation, to check new developments and techniques in image processing with Python, or for applications in computer vision.
More details
Other editions
Additional editions
Persons
Irshad Ahmad Ansari (PhD, SMIEEE20) has been working as an Assistant Professor Grade I in the Department of Electrical and Electronics Engineering at ABVIIITM, Gwalior, India, since June 2023. He has more than 70 publications, including 29 SCI/ SCIE journal papers, 28 international conference papers, 6 edited books, and 6 book chapters. He has been listed as the world's top 2% of researchers/scientists by Stanford University, USA (October, 2023).
Varun Bajaj (PhD, SMIEEE20) has been working as an Associate Professor in the discipline of Electronics and Communication Engineering at Maulana Azad National Institute of Technology Bhopal, India since Jan 2024. He is an Associate Editor of the IEEE Sensor Journal, Biomedical Signal Processing for Frontiers in Signal Processing, and Subject Editor-in-Chief of IET Electronics Letters. He has 170 publications, which include 104 journal papers, 35 conference papers, 13 books, and 18 book chapters. He has been listed in the world's top 2% of researchers/scientists by Stanford University, USA (October 2020, October 2021, October 2022, October 2023).
Content
Vol 2: Image Processing
Preface
Acknowledgements
Editor biographies
List of contributors
Contributor biographies
1 Basics of image analysis and manipulation using Python
2 Digital image processing using Python language
3 Review and implementation of image segmentation techniques in Python
4 Segmentation of digital images with region growing algorithm
5 Retinal layer segmentation in OCT images
6 Image denoising using wavelet thresholding technique in Python
7 Prostate cancer segmentation of peripheral zone and central gland regions in mpMRI: comparative analysis with deep neural network U-Net and its advanced models
8 Optical character recognition: transforming images into text
9 Automatic COVID-19 identification with a binary neural network using CT images
10 A review and implementation of image despeckling methods
11 Application of image processing and machine learning techniques for vegetation cover classification in precision agriculture
