DocumentCode
117824
Title
Modeling spatial uncertainty of imprecise information in images
Author
Pham, Tuan D.
Author_Institution
Center for Adv. Inf. Sci. & Technol., Univ. of Aizu, Aizu-Wakamatsu, Japan
fYear
2014
fDate
9-12 Dec. 2014
Firstpage
1
Lastpage
4
Abstract
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.
Keywords
fuzzy set theory; image classification; statistical analysis; fuzzy events; fuzzy sets; geostatistics; image classification; image imprecise information; information content description; pattern analysis; probability measure; spatial uncertainty modeling; Entropy; Feature extraction; Fuzzy sets; Measurement uncertainty; Probability distribution; Sensitivity; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Asia-Pacific Signal and Information Processing Association, 2014 Annual Summit and Conference (APSIPA)
Conference_Location
Siem Reap
Type
conf
DOI
10.1109/APSIPA.2014.7041514
Filename
7041514
Link To Document