An investigation of multi-modal fusion schemes is done using synthetic data generation to
determine how the data characteristics influence fusion. The goal is to select the best fusion …

While biometric fusion is a well-studied problem, most of fusion schemes cannot account for
missing data (incomplete score lists), that is commonly encountered in large-scale …

In this chapter we will discuss fusion (ie, combination) of multiple sources of information with
the goal of improving the performance of fingerprint systems. This topic is also known as …

In traditional research, data fusion is referred to as multi-sensor data fusion. The theory is
that data from multiple sources can be combined to provide more accurate, reliable and …

Multimodal biometric fusion is gaining more attraction among researchers. As multimodal
biometric consolidates the information from multiple biometric sources, the effective fusion of …

The fusion of different forensic modalities for arriving at a decision of whether the evidence
can be attributed to a known individual is considered. Since close similarity and high …

In this paper, we present Discriminant Correlation Analysis (DCA), a feature level fusion
technique that incorporates the class associations in correlation analysis of the feature sets …

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

The notion of combining redundant and complementary sensory data to achieve higher
quality information has been around for long time. For example, biological systems usually …

There is a growing interest in data fusion oriented to identification and authentication from
biometric traits and physiological signals, because of its capacity for combining multiple …