We examine the performance of multimodal biometric authentication systems using state-of-the-art Commercial Off-the-Shelf (COTS) fingerprint and face biometric systems on a population approaching 1,000 individuals. The majority of prior studies of multimodal biometrics have been limited to relatively low accuracy non-COTS systems and populations of a few hundred users. Our work is the first to demonstrate that multimodal fingerprint and face biometric systems can achieve significant accuracy gains over either biometric alone, even when using highly accurate COTS systems on a relatively large-scale population. In addition to examining well-known multimodal methods, we introduce new methods of normalization and fusion that further improve the accuracy.

Experimental studies show that multimodal biometric systems for small-scale populations perform better than single-mode biometric systems. We examine if such techniques scale to larger populations, introduce a methodology to test the performance of such systems, and assess the feasibility of using commercial off-the-shelf (COTS) products to construct deployable multimodal biometric systems. A key aspect of our approach is to leverage confidence level scores from preexisting single-mode data. An example presents a multimodal biometrics system analysis that explores various normalization and fusion techniques for face and fingerprint classifiers. This multimodal analysis uses a population of about 1000 subjects, a number ten-times larger than seen in any previously reported study. Experimental results combining face and fingerprint biometric classifiers reveal significant performance improvement over single-mode biometric systems.

We present the design and implementation of MultiKron PCI, a hardware performance monitor that can be plugged into any computer with a free PCI bus slot. The monitor provides a series of high-resolution timers, and the ability to monitor the utilization of the PCI bus. We also demonstrate how the monitor can be integrated with online performance monitoring tools such as the Paradyn parallel performance measurement tools to improve the overhead of key timer operations by a factor of 25. In addition, we present a series of case studies using the MultiKron hardware performance monitor to measure and tune high-performance parallel completing applications. By using the monitor, we were able to find and correct a performance bug in a popular implementation of the MPI message passing library that caused some communication primitives to run at one half their potential speed.