Image processing with Python : a practical approach / edited by Irshad Ahmad Ansari, Varun Bajaj.

Format:

Book

Contributor:

Ansari, Irshad Ahmad, editor.

Bajaj, Varun, editor.

Institute of Physics (Great Britain), publisher.

Series:

IOP (Series). Release 24.

IOP ebooks. 2024 collection.

[IOP release $release]

IOP ebooks. [2024 collection]

Language:

English

Subjects (All):

Image processing.

Python (Computer program language).

Local Subjects:

Image processing.

Python (Computer program language).

Physical Description:

1 online resource (various pagings) : illustrations (some color).

Place of Publication:

Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2024]

System Details:

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.

Biography/History:

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).

Summary:

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.

Contents:

1. Basics of image analysis and manipulation using Python / Akanksha Dixit

2. Digital image processing using Python language / Devanand Bhonsle, Ravi Mishra, Swati Hadke, Anupama Mohabansi, Prajakta Upadhye and Sheetal Mungale

3. Review and implementation of image segmentation techniques in Python / Siddharth Bhalerao, Sourabh Sahu and Saurabh Tewari

4. Segmentation of digital images with region growing algorithm / Amin Sakhaei and Zahra Ghanbari

5. Retinal layer segmentation in OCT images / P.V. Sudeep, V.R. Deepthi and G. Sreelekha

6. Image denoising using wavelet thresholding technique in Python / Devanand Bhonsle, Shruti Tiwari, Roshni Rahangdale, Manjushree Nayak, Ruhi Uzma Sheikh and Anu G. Pillai

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 / Anil B. Gavade, Rajendra B. Nerli, Pushkar Bansidhar Patil, Richa Ravi

Siddannavar, Venkata Siva Prasad Bhagavatula and Priyanka A. Gavade

8. Optical character recognition: transforming images into text / Nikhil Kushwaha, Om Asati and Mainak Sadhya

9. Automatic COVID-19 identification with a binary neural network using CT images / Rajveer S. Lalawat and Varun Bajaj

10. A review and implementation of image despeckling methods / Rishab Sarkar and P.V. Sudeep

11. Application of image processing and machine learning techniques for vegetation cover classification in precision agriculture / Atiya Khan, C.H. Patil, Amol D. Vibhute and Shankar Mali.

Notes:

"Version: 20240701"--Title page verso.

Includes bibliographical references.

Title from PDF title page (viewed on August 1, 2024).

Other Format:

Print version:

ISBN:

9780750359245

9780750359238

OCLC:

1451139811

Access Restriction:

Restricted for use by site license.