Digital Image Processing: Illustration using Python - Tapa blanda

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S. Esakkirajan is working as Professor in the Department of Instrumentation and Control Systems Engineering, PSG College of Technology, Coimbatore. He has twenty years of teaching experience. He has guided four research scholars in the area of signal and image processing. He has published Digital Signal Processing and Digital Image Processing textbooks published by McGraw Hill. He is coauthor of Digital Signal Processing: Illustration Using Python published by Springer. He was the organizing secretary of IEEE International Conference on “Machine Vision and Image Processing” in the year 2012. He has published papers in the field of signal and image processing in reputed journals and conferences.

T. Veerakumar is an associate professor in the Department of Electronics and Communication Engineering, National Institute of Technology, Goa. He graduated with a B.E. in Electronics and Communication Engineering from RVS College of Engineering Technology, Dindigul. Then, he did an M.E. degree in Applied Electronics from PSG College of Technology, Coimbatore, and a Ph.D. in Image Denoising from Anna University, Chennai. He coauthored the textbook titled Digital Image Processing and Digital Signal Processing, published by McGraw Hill. He is also coauthor of Digital Signal Processing: Illustration Using Python published by Springer. In addition, he has published around 60 research articles in reputed journals and conferences. His area of interest includes signal and image processing, biomedical image processing, object detection, and tracking. He is a member of IEEE.

Badri Narayan Subudhi received M.Tech. in Electronics and System Communication from National Institute of Technology, Rourkela, India, in 2008–2009. He worked for his PhD from Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India, in year 2014 (degree from Jadavpur University). Currently, he is serving as an associate professor at Indian Institute of Technology Jammu, India. Prior to this, he was working as an assistant professor at NIT Goa from July 2014 to March 2017. He received CSIR senior research fellowship for the year 2011–2015. He was nominated as the Young Scientist Awardees by Indian Science Congress Association for the year 2012–2013. He was awarded with Young Scientist Travel Grant Award from DST, Government of India, and Council of Scientific and Industrial Research, India, in the year 2011. He is the recipient of Bose-Ramagnosi Award for the year 2010 from DST, Government of India under India-Trento Programme for Advanced Research (ITPAR). He was a visiting scientist at the University of Trento, Italy, during August 2010 to February 2011. His research interests include video processing, image processing, medical image processing, machine learning, pattern recognition, and remote sensing image analysis. He coauthored the textbook titled “Digital Signal Processing,” published by McGraw Hill. He is also coauthor of Digital Signal Processing: Illustration Using Python published by Springer. He has published around 80 research papers in reputed journals and conferences. He is a senior member of IEEE.

De la contraportada

Digital image processing plays a crucial role in facilitating efficient storage, transmission, manipulation, and retrieval of images. Python, renowned for its open-source nature and strong community support, offers a user-friendly platform with extensive image processing capabilities through libraries such as computer vision and scikit-learn.
This textbook serves as a practical guide to digital image processing using Python, presenting fundamental concepts, techniques, and algorithms with illustrative examples in Python. Each chapter begins with clear learning objectives and concludes with exercises and multiple-choice questions for self-assessment. Drawing from a diverse range of sources including research articles and books, the references provided at the end of each chapter encourage further exploration.
Tailored for undergraduate and postgraduate students, research scholars, engineers, and faculty specializing in image processing, it assumes a foundational understanding of set theory, matrix algebra, probability, and random variables.