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Modeling spatial uncertainty of imprecise information in images.
Aizu Research Cluster for Medical Engineering and Informatics Center for Advanced Information Science and Technology The University of Aizu Aizu-Wakamatsu, Fukushima 965-8580, Japan.ORCID iD: 0000-0002-4255-5130
2014 (English)Conference paper (Refereed)Text
Abstract [en]

The description of information content in images is imprecise in nature. Quantification of uncertainty in images for pattern analysis has been addressed with the theories of probability and fuzzy sets. In this paper, an approach for modeling the spatial uncertainty of images is proposed in the setting of geostatistics and probability measure of fuzzy events. The proposed approach can be utilized to extract an effective feature for image classification.

Place, publisher, year, edition, pages
2014. 1-4 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:liu:diva-128583DOI: 10.1109/APSIPA.2014.7041514OAI: diva2:935164
2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)
Available from: 2016-06-10 Created: 2016-05-25 Last updated: 2016-06-27

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Pham, Tuan D
Computer Vision and Robotics (Autonomous Systems)

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ReferencesLink to record
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