Serial fusion of multi-modal biometric systems
This work addresses the under-investigated issue of serial fusion for biometric systems, which could improve performance in security and identification applications, but it appears incremental as it builds on previous work.
The authors tackled the problem of serial fusion in multi-modal biometric systems by proposing a novel theoretical framework for performance assessment, and they theoretically evaluated performance benefits and parameter estimation errors using preliminary experiments on NIST Biometric Score Set 1.
Serial, or sequential, fusion of multiple biometric matchers has been not thoroughly investigated so far. However, this approach exhibits some advantages with respect to the widely adopted parallel approaches. In this paper, we propose a novel theoretical framework for the assessment of performance of such systems, based on a previous work of the authors. Benefits in terms of performance are theoretically evaluated, as well as estimation errors in the model parameters computation. Model is analyzed from the viewpoint of its pros and cons, by mean of preliminary experiments performed on NIST Biometric Score Set 1.