Approximation of Euclidean Metric by Digital Distances / by Jayanta Mukhopadhyay

By:

Mukhopadhyay, Jayanta [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Springer eBook CollectionPublisher: Singapore : Springer Singapore, 2020Publisher: Singapore : Imprint: Springer, 2020Edition: 1st ed. 2020Description: 1 Online-Ressource(XX, 144 p. 31 illus., 5 illus. in color.)ISBN:

9789811599019

Subject(s):

Additional physical formats: 9789811599002 | 9789811599026 | Erscheint auch als: 9789811599002 Druck-Ausgabe | Erscheint auch als: 9789811599026 Druck-AusgabeDDC classification:

006.6 23
006.37 23

DOI: DOI: 10.1007/978-981-15-9901-9Online resources:

Summary: Geometry, Space and Metrics -- Digital distances: Classes and hierarchies -- Error analysis analytical approaches -- Linear combination of digital distances.Summary: 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. .PPN: PPN: 1743803982Package identifier: Produktsigel: ZDB-2-SCS | ZDB-2-SEB | ZDB-2-SXCS

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