Approximation of Euclidean Metric by Digital Distances

Mukhopadhyay, Jayanta.

Approximation of Euclidean Metric by Digital Distances [electronic resource] / by Jayanta Mukhopadhyay. - 1st ed. 2020. - XX, 144 p. 31 illus., 5 illus. in color. online resource.

Geometry, Space and Metrics -- Digital distances: Classes and hierarchies -- Error analysis analytical approaches -- Linear combination of digital distances.

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. .

9789811599019

10.1007/978-981-15-9901-9 doi


Computer vision.
Pattern recognition systems.
Functional analysis.
Computer science--Mathematics.
Discrete mathematics.
Computer Vision.
Automated Pattern Recognition.
Functional Analysis.
Discrete Mathematics in Computer Science.

TA1634

006.37
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