Information fusion is a key step in multimodal biometric systems. The fusion of information
can occur at different levels of a recognition system, ie, at the feature level, matching-score …

Automatically verifying the identity of a person by means of biometrics (eg, face and
fingerprint) is an important application in our day-to-day activities such as accessing banking …

In a multimodal biometric system, the effective fusion method is necessary for combining
information from various single modality systems. In this paper the performance of sum rule …

The rising demand for high security and reliable authentication schemes, led to the
development of the unimodal biometric system so that the multimodal biometric system has …

Multimodal biometrics technology consolidates information obtained from multiple sources
at sensor level, feature level, match score level, and decision level. It is used to increase …

A multimodal biometric system integrates information from multiple biometric sources to
compensate for the limitations in performance of each individual biometric system. We …

This paper presents a new evolutionary approach for adaptive combination of multiple
biometrics to ensure the optimal performance for the desired level of security. The adaptive …

The performance of a biometric system that relies on a single biometric modality (eg,
fingerprints only) is often stymied by various factors such as poor data quality or limited …

Bimodal biometrics has been found to outperform single biometrics and are usually
implemented using the matching score level or decision level fusion, though this fusion will …

Multimodal biometric systems consolidate the evidence presented by multiple biometric
sources and typically provide better recognition performance compared to systems based on …