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Feature Based Defuzzification at Increased Spatial Resolution
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: Combinatorial Image Analysis: 11th International Workshop, IWCIA 2006, 2006, 131-143 p.Conference paper, Published paper (Refereed)
Abstract [en]

Defuzzification of fuzzy spatial sets by feature distance minimization, recently proposed as an alternative to crisp segmentation, is studied further. Fully utilizing information available in a fuzzy (discrete) representation of a continuous shape, we present an improved defuzzification method, such that the crisp discrete representation of a fuzzy set is generated at an increased spatial resolution, compared to the resolution of the fuzzy set. The correspondence between a fuzzy and a crisp set is established through a distance between their representations based on selected features, where the different resolutions of the images to compare are taken into account. The performance of the method is tested on both synthetic and real images.

Place, publisher, year, edition, pages
2006. 131-143 p.
Series
Lecture notes in computer science, ISSN 0302-9743 ; 4040
Keyword [en]
fuzzy sets, defuzzification, multigrid resolution, distance measure, feature estimates
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:uu:diva-18176DOI: 10.1007/11774938ISBN: 978-3-540-35153-5 (print)OAI: oai:DiVA.org:uu-18176DiVA: diva2:45948
Available from: 2006-12-19 Created: 2006-12-19 Last updated: 2010-05-07Bibliographically approved

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Computer Vision and Robotics (Autonomous Systems)

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