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. 2014 Jan 28:2014:780835.
doi: 10.1155/2014/780835. eCollection 2014.

Optimization of a biometric system based on acoustic images

Alberto Izquierdo Fuente  1 , Lara Del Val Puente  2 , Juan J Villacorta Calvo  1 , Mariano Raboso Mateos  3
Affiliations

Optimization of a biometric system based on acoustic images

Alberto Izquierdo Fuente et al. ScientificWorldJournal. .

Abstract

On the basis of an acoustic biometric system that captures 16 acoustic images of a person for 4 frequencies and 4 positions, a study was carried out to improve the performance of the system. On a first stage, an analysis to determine which images provide more information to the system was carried out showing that a set of 12 images allows the system to obtain results that are equivalent to using all of the 16 images. Finally, optimization techniques were used to obtain the set of weights associated with each acoustic image that maximizes the performance of the biometric system. These results improve significantly the performance of the preliminary system, while reducing the time of acquisition and computational burden, since the number of acoustic images was reduced.

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Figures

Figure 1
Figure 1
Functional description block diagram.
Figure 2
Figure 2
Transmitter and receiver arrays.
Figure 3
Figure 3
Hardware architecture block diagram.
Figure 4
Figure 4
Scanning and positioning area.
Figure 5
Figure 5
Person positions.
Figure 6
Figure 6
Acoustic images. x-axis: angle (degrees); y-axis: range (m).
Figure 7
Figure 7
Functions FMR and FNMR versus distance d.
Figure 8
Figure 8
ROC.
Figure 9
Figure 9
Equal error rate versus number of removed images.
Figure 10
Figure 10
ROC function with 12 images: unitary weights versus optimized weights.
Figure 11
Figure 11
ROC function with 16 images: unitary weights versus optimized weights.
Figure 12
Figure 12
ROC function with 12 images versus 16 images with optimized weights.
See this image and copyright information in PMC

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