DocumentCode :
1441785
Title :
Adaptive Local Fusion With Fuzzy Integrals
Author :
Abdallah, A.C.B. ; Frigui, Hichem ; Gader, Paul
Author_Institution :
Bloomberg LP, New York, NY, USA
Volume :
20
Issue :
5
fYear :
2012
Firstpage :
849
Lastpage :
864
Abstract :
We propose a novel method for fusing different classifiers outputs. Our approach, called context extraction for local fusion with fuzzy integrals (CELF-FI), is a local approach that adapts a fuzzy integrals fusion method to different regions of the feature space. It is based on a novel objective function that combines context identification and multialgorithm fusion criteria into a joint objective function. This objective function consists of two terms: The first is designed to produce compact clusters, called contexts, and the second is designed to produce Sugeno measures for fuzzy integral fusion for each context. The terms are optimized simultaneously via alternating optimization. To test a new sample, first, its features (extracted by each algorithm) are used to assign it to each context with a fuzzy membership degree. Second, the sample confidence values (assigned by each algorithm) are fused within each context using the learned context fusion parameters. Then, the context-dependent partial confidence values are weighted by the membership degrees and averaged over all contexts to produce a final confidence value. We illustrate the performance of CELF using synthetic data, and we apply it to the problem of landmine detection using ground penetrating radar and wideband electromagnetic induction. Our extensive experiments have indicated that the proposed fusion approach outperforms all individual classifiers, the global fuzzy integral fusion method, and the basic local fusion with linear aggregation.
Keywords :
electromagnetic induction; fuzzy set theory; ground penetrating radar; landmine detection; optimisation; pattern classification; radar computing; sensor fusion; CELF-FI; Sugeno measures; adaptive local fusion; alternating optimization; classifiers outputs; context extraction for local fusion with fuzzy integrals; context identification; context-dependent partial confidence values; fuzzy membership degree; global fuzzy integral fusion method; ground penetrating radar; landmine detection; linear aggregation; multialgorithm fusion criteria; synthetic data; wideband electromagnetic induction; Clustering algorithms; Context; Feature extraction; Indexes; Partitioning algorithms; Testing; Training; Classification; classifier fusion; clustering; fuzzy integrals; local fusion;
fLanguage :
English
Journal_Title :
Fuzzy Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6706
Type :
jour
DOI :
10.1109/TFUZZ.2012.2187062
Filename :
6146419
Link To Document :
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