DocumentCode :
2748413
Title :
Use of fuzzy clustering for determining mass functions Dempster-Shafer theory
Author :
Bentabet, Layachi ; ZHU, Yue Min ; Dupuis, Olivier ; KAFTANDJIA, Valérie ; Babot, D. ; ROMBAUT, Michéle
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
1462
Abstract :
This paper presents a new approach of automatically determining mass functions in Dempster-Shafer (evidence) theory from the grey levels of images. To achieve this, two underlying aspects have been in particular investigated in the context of segmentation of images from two different sources. The first one concerns the determination of mass function using the fuzzy C-means clustering, and the second one deals with the matching of clusters in the two images being fused. The proposed approach is illustrated with the aid of simulations and examples on physical images
Keywords :
fuzzy set theory; image matching; image segmentation; pattern clustering; sensor fusion; uncertainty handling; Dempster-Shafer theory; data fusion; fuzzy clustering; image matching; image segmentation; mass functions; Data structures; Equations; Fuzzy logic; Fuzzy sets; Histograms; Image segmentation; Length measurement; Measurement uncertainty; Pixel; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-5747-7
Type :
conf
DOI :
10.1109/ICOSP.2000.893377
Filename :
893377
Link To Document :
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