This paper presents an investigation into the effects, on the accuracy of multimodal biometrics, of introducing unconstrained cohort normalisation (UCN) into the score-level fusion process. Whilst score normalisation has been widely used in voice biometrics, its effectiveness in other biometrics has not been previously investigated. This study aims to… (More)
This paper addresses the performance of various statistical data fusion techniques for combining the complementary score information in speaker verification. The complementary verification scores are based on the static and delta cepstral features. Both LPCC (Linear prediction-based cepstral coefficients) and MFCC (mel-frequency cepstral coefficients) are… (More)
Surveillance and safety is immensely important in general, while explicitly in case of critical applications, such as oil carrying pipelines from wells to refinery and then to the sea ports for further transportation. Surveillance and safety systems with different combinations already has been proposed for critical infrastructures to make them safe and… (More)
A new approach to enhancing the accuracy of multimodal biometrics is investigated. The proposed approach, which involves combining score normalisation and qualitative-based fusion, is shown to considerably improve the accuracy of multimodal biometrics under different data conditions.
Verification using biometrics has become in the last few years a key issue in security and privacy. Intensive search is being focusing on improving verification performance and quality by fusing multi biometric modalities. Several fusion techniques have been proposed in the current literature. This paper proposes hybrid artificial intelligent tools such as… (More)