Approximation of Euclidean Metric by Digital Distances (Paperback, 1st ed. 2020)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Release date:	December 2020
First published:	2020
Authors:	Jayanta Mukhopadhyay
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	144
Edition:	1st ed. 2020
ISBN-13:	978-981-15-9900-2
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Functional analysis Books > Computing & IT > Applications of computing > Image processing > General
LSN:	981-15-9900-9
Barcode:	9789811599002

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