Method for determining Classification Significant Features from Acoustic Signature of Mine-like buried objects (CROSBI ID 477717)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Antonić, Davor ; Žagar, Mario
engleski
Method for determining Classification Significant Features from Acoustic Signature of Mine-like buried objects
Good feature selection method is an essential step in a classification system. That is especially true for detection systems that have to deal with low signal-to-noise ratio, and varying background conditions, which is the case for landmine detection systems. Proposed method analyzes spectrum of a signal collected from the microphone placed inside the deminers prodder and extracts set of features with best discrimination ability. Feature selection is performed in two stages. First, huge initial set of near 2*10E4 features is reduced to approximately 100 features and from reduced set best feature subset is selected. Algorithm was successfully applied to the set of unified samples from different materials, as well as on the real landmines and harmless objects.
feature extraction; signal analysis; classification; landmine detection
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Podaci o prilogu
769-x.
2000.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 15th World Conference on Non-Destructive Testing
Rim: WCNDT
Podaci o skupu
15th World Conference on Non-Destructive Testing
predavanje
15.10.2000-21.10.2000
Rim, Italija