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Weighted distances based on neighbourhood sequences
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
2007 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 28, no 15, 2029-2036 p.Article in journal (Refereed) Published
Abstract [en]

By combining weighted distances and distances based on neighbourhood sequences, a new family of distance functions with potentially low rotational dependency is obtained. The basic theory for these distance functions, including functional form of the distance between two points, is presented. By minimizing an error function, the weights and neighbourhood sequence that give the distance function with the lowest rotational dependency are derived. To verify that the low rotational dependency of the proposed distance function is valid also in applications, the constrained distance transform on a binary image is computed and compared with some traditionally used distance functions.

Place, publisher, year, edition, pages
2007. Vol. 28, no 15, 2029-2036 p.
Keyword [en]
Digital geometry, Distance functions, Neighbourhood sequences, Weighted distance, Discrete geometry
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:uu:diva-11899DOI: 10.1016/j.patrec.2007.05.016ISI: 000250377600013OAI: oai:DiVA.org:uu-11899DiVA: diva2:39668
Available from: 2007-11-04 Created: 2007-11-04 Last updated: 2017-12-11Bibliographically approved

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Strand, Robin

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