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This is expanded through the development of algorithms that consider multiple biometric systems [31].
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It is likely, however, that multiple biometric retail systems will make their way into the market.
Compared to uni-biometric systems, multi-biometric systems, which fuse multiple biometric features, can improve recognition accuracy and security.
One solution to these problems is to use multiple biometric traits for recognition, and systems of this type are known as multi-modal biometric systems [5].
Due to the sensitivity of BCSs, more user-cooperation (compared to conventional biometric systems) or multiple enrollment samples [216] are demanded in order to decrease intra-class variation, while sensoring and preprocessing require improvement as well.
However, in general, multimodal biometric systems require multiple sensors, which result in high developmental costs.
On national-sized biometric systems, the use of multiple biometric characteristics has been found to significantly improve the accuracy and reliability especially in challenging identification scenarios [6], while recognition systems based on a single biometric indicator often have to contend with unacceptable error rates [7].
Biometric systems for today's high security applications must meet stringent performance requirements; fusing multiple biometrics can help lower system error rates.
To improve system accuracy, there is strong interest in research to combine multiple biometric characteristics for multimodal personal identity authentication [19, 20].
The proposed system is based on a score fusion which can effectively combine the discriminative power of multiple biometric traits.
-- Plans to deploy biometric systems to enhance domestic counterterrorism efforts.
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