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Path-Based Distance Functions in n-Dimensional Generalizations of the Face- and Body-Centered Cubic Grids
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
Faculty of Informatics, University of Debrecen, Debrecen, Hungary.
2009 (English)In: Discrete Applied Mathematics, ISSN 0166-218X, E-ISSN 1872-6771, Vol. 157, no 16, 3386-3400 p.Article in journal (Refereed) Published
Abstract [en]

Path-based distance functions are defined on n-dimensional generalizations of the face-centered cubic and body-centered cubic grids. The distance functions use both weights and neighborhood sequences. These distances share many properties with traditional path-based distance functions, such as the city-block distance, but are less rotational dependent. For the three-dimensional case, we introduce four different error functions which are used to find the optimal weights and neighborhood sequences that can be used to define the distance functions with low rotational dependency.

Place, publisher, year, edition, pages
Elsevier , 2009. Vol. 157, no 16, 3386-3400 p.
Keyword [en]
digital geometry, distance functions, non-standard grids
National Category
Computer and Information Science
Research subject
Computerized Image Analysis
Identifiers
URN: urn:nbn:se:uu:diva-109539DOI: 10.1016/j.dam.2009.02.008ISI: 000271375400004ISBN: 978-3-540-89645-6 (print)OAI: oai:DiVA.org:uu-109539DiVA: diva2:272761
Available from: 2009-10-16 Created: 2009-10-16 Last updated: 2017-12-12Bibliographically approved

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Publisher's full texthttp://dx.doi.org/10.1016/j.dam.2009.02.008

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Strand, Robin

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