Biometric face recognition method using graphics processing unit system

The expansion of biometric applications and databases is worrying. Processing extensive or sophisticated biometric data results in longer wait times, which might restrict application usefulness. This work focuses on accelerating the processing of biometric data and proposes a parallel method of data processing that exceeds the capabilities of a central processing unit (CPU). The combination of the graphics processing unit (GPU) and compute unified device architecture (CUDA) results in at least three times the processing speed of a published accurate and secure multimodal biometric system. The GPU-assisted approach beats the CPU-only implementation when saturating the CPU-only performance with more people than the available thread count. The GPU-assisted solution is also proven to have the same accuracy as the original system, indicating accuracy and processing performance improvements in the demanding big data environment.