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Feature Based Defuzzification in Z² and Z³ Using a Scale Space Approach
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.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
2006 (English)In: Discrete Geometry for Computer Imagery 13th International Conference, DGCI 2006, Szeged, Hungary, October 25-27, 2006. Proceedings: DGCI 2006, 2006, 379-390 p.Conference paper, Published paper (Refereed)
Abstract [en]

A defuzzification method based on feature distance minimization is further improved by incorporating into the distance function feature values measured on object representations at different scales. It is noticed that such an approach can improve defuzzification results by better preserving the properties of a fuzzy set; area preservation at scales in-between local (pixel-size) and global (the whole object) provides that characteristics of the fuzzy object are more appropriately exhibited in the defuzzification. For the purpose of comparing sets of different resolution, we propose a feature vector representation of a (fuzzy and crisp) set, utilizing a resolution pyramid. The distance measure is accordingly adjusted. The defuzzification method is extended to the 3D case. Illustrative examples are given.

Place, publisher, year, edition, pages
2006. 379-390 p.
Series
Lecture notes in computer science, ISSN 0302-9743 ; 4245
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-12444DOI: 10.1007/11907350_32ISBN: 978-3-540-47651-1 (print)OAI: oai:DiVA.org:uu-12444DiVA: diva2:40213
Available from: 2007-12-20 Created: 2007-12-20 Last updated: 2010-06-14Bibliographically approved

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Lindblad, JoakimSladoje, Natasa

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