Ebook: Approximation of Euclidean Metric by Digital Distances
Author: Jayanta Mukhopadhyay
- Tags: Computer Science, Image Processing and Computer Vision, Pattern Recognition, Functional Analysis, Discrete Mathematics in Computer Science
- Year: 2020
- Publisher: Springer Singapore
- Edition: 1st ed.
- Language: English
- pdf
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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