Title
Generalized Choquet fuzzy integral fusion
Abstract
Sensor fusion plays an important role in many application domains. No single source of information (decision or feature) can provide the absolute solution when detection and recognition problems become more complex and computationally expensive (e.g., in land mine detection). However, complementary information can be derived from multiple sources. In this paper, we build a decision-based fusion system based on the uncertainty approach utilizing an extension of the Choquet fuzzy integral (generalized Choquet fuzzy integral, GCFI). The difference between the standard Choquet fuzzy integral and the GCFI is that the GCFI integrates vectors of fuzzy numbers instead of vectors of numeric membership values. The system is applied to a land mine detection problem. The fuzzy vectors represent uncertainty in both the confidence and location estimates of several detection algorithm outputs. The results show a huge improvement in the probability of detection and a reduction in the false alarm rate over the best algorithm and two numeric fusion schemes, i.e., the average confidence and a decision level fusion with the numeric Choquet fuzzy integral. The GCFI obtains 100% probability of detection at 0.02 false alarm rate per square meter on a large test set, whereas the best detection algorithm and the average confidence achieve only 91% and 96% probability of detection at that rate. Additionally, at 0.02 false alarm rate, decision level fusion with the numeric Choquet fuzzy integral reaches only 87% probability of detection.
Year
DOI
Venue
2002
10.1016/S1566-2535(01)00054-9
Information Fusion
Keywords
Field
DocType
Fuzzy vectors,Generalized Choquet fuzzy integral,Decision fusion,Land mine detection
Pattern recognition,Fuzzy classification,Fuzzy set operations,Fuzzy logic,Fuzzy measure theory,Sensor fusion,Artificial intelligence,Constant false alarm rate,Fuzzy number,Membership function,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
3
1
1566-2535
Citations 
PageRank 
References 
46
2.47
12
Authors
3
Name
Order
Citations
PageRank
S. Auephanwiriyakul124639.45
James M. Keller23201436.69
Paul Gader31909196.70