DocumentCode :
344612
Title :
Aspects of high level computer vision using fuzzy sets
Author :
Keller, James M. ; Matsakis, Pascal
Author_Institution :
Dept. of Comput. Sci. & Eng., Missouri Univ., Columbia, MO, USA
Volume :
2
fYear :
1999
fDate :
22-25 Aug. 1999
Firstpage :
847
Abstract :
Fuzzy set theory is making many inroads into the handling of uncertainty in various aspects of image processing and computer vision. High level computer vision is a place that holds great potential for fuzzy sets because of its natural linguistic capabilities. Scene description, i.e., the language-based representation of regions and their relationships, for either humans or higher automated reasoning provides an excellent opportunity. In this paper we discuss aspects of scene interpretation involving linguistic descriptions of spatial relations between image objects.
Keywords :
computer vision; fuzzy set theory; automated reasoning; fuzzy set theory; high-level computer vision; image objects; image processing; linguistic descriptions; natural linguistic capabilities; scene description; scene interpretation; spatial relations; Computer vision; Fuzzy control; Fuzzy sets; Histograms; Humans; Image analysis; Image processing; Layout; Pattern recognition; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International
Conference_Location :
Seoul, South Korea
ISSN :
1098-7584
Print_ISBN :
0-7803-5406-0
Type :
conf
DOI :
10.1109/FUZZY.1999.793059
Filename :
793059
Link To Document :
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