Title :
Modeling spatial uncertainty of imprecise information in images
Author_Institution :
Center for Adv. Inf. Sci. & Technol., Univ. of Aizu, Aizu-Wakamatsu, Japan
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;
Conference_Titel :
Asia-Pacific Signal and Information Processing Association, 2014 Annual Summit and Conference (APSIPA)
Conference_Location :
Siem Reap
DOI :
10.1109/APSIPA.2014.7041514
