An Efficient Algorithm for Multimodal Biometric Face Recognition using Speech Signal
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Abstract
Multimodal biometric systems for today’s high security applications must meet stringent performance requirements. The fusion of
multiple biometrics helps to minimize the system error rates. Fusion methods include processing biometric modalities sequentially until an
acceptable match is obtained. More sophisticated methods will combine scores from separate classifiers for each modality. Multi algorithm
approach employs a single biometric sample acquired from single sensor. Two or more different algorithms process this acquired sample. The
individual results are combined to obtain an overall recognition result. This approach is attractive, both from an application and research point of
view. In recent years much advancement have been made in face recognition techniques to cater to the challenges such as pose, expression,
illumination, aging and disguise. However, due to advances in technology, there are new emerging challenges for which the performance of face
recognition systems degrades and plastic/cosmetic surgery is one of them. In this paper we comment on the effect of plastic surgery face image
in multimodal biometric face recognition using text dependent speech signal.
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Keywords: Multimodal biometric system; plastic surgery face image; speech signal and matching level fusion.
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