Fawaz Alsaade

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BIOMETRICS Fawaz Alsaade, Aladdin Ariyaeeinia, Amit Malegaonkar, Surosh Pillay University of Hertfordshire, Hatfield, UK Abstract 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(More)
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)
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)
This paper proposes an approach to enhancing the accuracy of multimodal biometrics in uncontrolled environments. Variation in operating conditions results in mismatch between the training and test material, and thereby affects the biometric authentication performance regardless of this being unimodal or multimodal. The paper proposes a technique to reduce(More)
Genetic Algorithms have attained overwhelming attention in successfully solving many computer vision problems. This paper addresses a robust face detection method with images in diversified backgrounds employing genetic algorithm. The system is organized with skin color segmentation in YCbCr color space. Since the computational cost for genetic algorithm is(More)
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