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Mulitmodal Biometric Systems

Mulitmodal Biometric Systems. Munir Bandukwala Rajesh Subramanian. Introduction . Biometric systems using single biometrics have to contend with Noisy data. Restricted degrees of freedom. Non universality of data. Unacceptable error rates. Intoduction-contd… .

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Mulitmodal Biometric Systems

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  1. Mulitmodal Biometric Systems Munir Bandukwala Rajesh Subramanian

  2. Introduction • Biometric systems using single biometrics have to contend with • Noisy data. • Restricted degrees of freedom. • Non universality of data. • Unacceptable error rates.

  3. Intoduction-contd… • Multibiometric systems reduce these problems by providing multiple evidences of the same entity. • These systems improve overall performance. • Multimodal systems also make spoofing difficult. • By prompting for a random set of biometric traits, such systems ensure a built in ‘liveness test’.

  4. Problems involved • A multimodal system needs a particular ‘fusion scheme’ to integrate the data from multiple modalities. • Several fusion schemes are available in the literature • Sum Rule [1] • Decision trees [1] • Linear Discriminant Analysis [1]

  5. Problems involved-contd… • Further schemes like: • Learning user specific matching thresholds • Weighting of individual biometric traits or • A combination of the above also seem to bolster performance [2]

  6. Problem Statement • We plan to propose a fusion system that will provide an integration scheme for Fingerprint, Hand Geometry and Signature. • We propose to find a scheme providing better results. • The fusion will be at the matching score level.

  7. References [1] Information Fusion in Biometrics-Arun Ross and Anil Jain [2]Learning User-specific parameters in a multibiometric system-Anil K. Jain and Arun Ross

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