DocumentCode :
3183530
Title :
Fuzzy logic and the principle of least commitment in computer vision
Author :
Keller, James M. ; Gader, Paul
Author_Institution :
Dept. of Electr. & Comput. Eng., Missouri Univ., Columbia, MO, USA
Volume :
5
fYear :
1995
fDate :
22-25 Oct 1995
Firstpage :
4621
Abstract :
The application of fuzzy logic to computer vision processes has grown rapidly. The appeal of such techniques stems, at least partially, from the fact that they naturally maintain multiple hypotheses to varying degrees until a crisp decision must be made. This satisfies the principle of least commitment, originally stated by David Man for the development of intelligent computer vision algorithms. In this paper, we demonstrate fuzzy set theory´s support of this principle with three examples from midlevel vision
Keywords :
character recognition; computer vision; fuzzy logic; fuzzy neural nets; fuzzy set theory; object recognition; computer vision; fuzzy logic; fuzzy neural networks; fuzzy set theory; intelligent vision; least commitment principle; object recognition; Additive noise; Application software; Books; Character recognition; Computer vision; Fuzzy logic; Fuzzy set theory; Handwriting recognition; Image segmentation; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2559-1
Type :
conf
DOI :
10.1109/ICSMC.1995.538524
Filename :
538524
Link To Document :
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