Approximation of Euclidean Metric by Digital Distances (PDF)
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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.
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, and 2008. He
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).
- Autor: Jayanta Mukhopadhyay
- 2020, 1st ed. 2020, 144 Seiten, Englisch
- Verlag: Springer Nature Singapore
- ISBN-10: 9811599017
- ISBN-13: 9789811599019
- Erscheinungsdatum: 02.12.2020
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- Größe: 2.76 MB
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