Overview
- Covers the topic of digital distances and their Euclidean approximation comprehensively
- Includes recent results and advancement in the theory of digital distances
- Summarizes properties of different classes of digital distances, and highlights a set of good distances having good approximation properties of the Euclidean metrics
- Includes the theory and results on the properties of different distance functions that will have applications in various pattern recognition techniques
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Table of contents (6 chapters)
Keywords
About this book
This book discusses different types of distance functions defined in an n-D integral space for their usefulness in approximating the Euclidean metric. It discusses the properties of these distance functions and presents various kinds of error analysis in approximating Euclidean metrics. It also presents a historical perspective on efforts and motivation for approximating Euclidean metrics by digital distances from the mid-sixties of the previous century. The book also contains an in-depth presentation of recent progress, and new research problems in this area.
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Authors and Affiliations
About the author
Dr. Jayanta Mukhopadhyay (Mukherjee) received his B.Tech., M.Tech., and Ph.D. degrees in Electronics and Electrical Communication Engineering from the Indian Institute of Technology (IIT), Kharagpur, in 1985, 1987, and 1990, respectively. He joined the faculty of the Department of Electronics and Electrical Communication Engineering at IIT, Kharagpur, in 1990, and later moved to the Department of Computer Science and Engineering where he is presently a Professor. He served as the Head of the Computer and Informatics Center at IIT, Kharagpur, from September 2004 to July 2007. He also served as the Head of the Department of Computer Science and Engineering and the School of Information and Technology from April, 2010 to March, 2013.
He was a Humboldt Research Fellow at the Technical University of Munich in Germany for one year in 2002. He has also held short-term visiting positions at the University of California, Santa Barbara, University of Southern California, and the National University of Singapore. His research interests are in image processing, pattern recognition, computer graphics, multimedia systems, and medical informatics. He has supervised 15 doctoral students, and published more than 200 research papers in journals and conference proceedings in these areas. He has authored a book on “Image and Video Processing in the compressed domain”, and co-authored a book on “Digital Geometry in Image Processing”. Dr. Mukhopadhyay is a senior member of the IEEE. He also holds life membership of various professional societies in his areas of expertise such Indian Association of Medical Informatics (IAMI), Telemedicine Society of India (TSI), Indian Unit of Pattern Recognition and Artificial Intelligence (IUPRAI, India). He has served as a member of technical program committees of several national and international conferences, and served as Program Co-Chairs of Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP) in 2000, and2008. He also served as Program Chairs of the International Workshop on Recent Advances in Medical Informatics in 2013 and 2014. He is serving as a member of the editorial boards of Journal of Visual Communication and Image Representation, and Pattern Recognition Letters published by Elsevier.
He received the Young Scientist Award from the Indian National Science Academy in 1992, and is a Fellow of the Indian National Academy of Engineering (INAE).
Bibliographic Information
Book Title: Approximation of Euclidean Metric by Digital Distances
Authors: Jayanta Mukhopadhyay
DOI: https://doi.org/10.1007/978-981-15-9901-9
Publisher: Springer Singapore
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020
Softcover ISBN: 978-981-15-9900-2Published: 03 December 2020
eBook ISBN: 978-981-15-9901-9Published: 02 December 2020
Edition Number: 1
Number of Pages: XX, 144
Number of Illustrations: 26 b/w illustrations, 5 illustrations in colour
Topics: Image Processing and Computer Vision, Pattern Recognition, Functional Analysis, Discrete Mathematics in Computer Science