Master Thesis - Department of Computer Science
Master Thesis - Department of Computer Science
Master Thesis - Department of Computer Science
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• Parallel Mode: This operational mode consists in completing the combina-<br />
tion <strong>of</strong> the modalities simultaneously. Different modalities operate indepen-<br />
dently and their results are combined using an appropriate fusion scheme.<br />
• Serial Mode: This operational mode consists in completing the combination<br />
<strong>of</strong> the modalities one after the other, as it permits to reduce the population<br />
at each stage before the following modality is used. The decision could thus<br />
be taken before all the remaining biometrics are acquired, reducing consider-<br />
ably the processing duration. Here the outcome <strong>of</strong> one modality affects the<br />
processing <strong>of</strong> the subsequent modalities.<br />
• Hierarchical Mode: This operational mode consists in completing the com-<br />
bination <strong>of</strong> the modalities in a hierarchical scheme, like a tree structure, when<br />
the number <strong>of</strong> classifiers is large. This architecture can also allow the user to<br />
decide which modality he/she would present first. Finally, if the system is faced<br />
with the task <strong>of</strong> identifying the user from a large database, it can utilize the<br />
outcome <strong>of</strong> each modality to successively prune the database, thereby making<br />
the search faster and more efficient. An example <strong>of</strong> a cascaded multibiometric<br />
system is the one proposed by Hong and Jain in [48].<br />
Most proposed multibiometric systems have a parallel architecture [115, 106]. But<br />
the choice <strong>of</strong> system architecture depends on the application. User-friendly and less<br />
security like ATMs can use hierarchical mode. On the other hand parallel mode<br />
are well suited for applications where security is <strong>of</strong> paramount importance (military<br />
installations).<br />
2.3.2 Fusion Scenarios<br />
Multimodal biometric systems overcome some <strong>of</strong> the limitations <strong>of</strong> unimodal biometric<br />
systems by consolidating the evidence obtained from different sources (see Fig. 2.10).<br />
The sources are given below:<br />
• Single Biometry, Multiple Sensors: The same biometric is acquired by<br />
different sensors and combined to complete and improve the recognition process<br />
(e.g. optical and solid-state fingerprint sensors). The use <strong>of</strong> multiple sensors<br />
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