Human biometric recognition systems are becoming more prevalent and essential in the personal identification applications market. This market spans the commercial and the military sectors to include a myriad of identification applications to include everything from secure entrance, to time card clocks, to casino players club enrollment, to automobiles that recognizer their drivers, to money transaction systems, to weapons that recognize their owners, etc. A general Fast Pattern Recognition (FPR) algorithm has been developed that demonstrates superior performance in facial recognition (visible light and IR) and fingerprint recognition even under degraded conditions. This same algorithm has also demonstrated exceptional performance on voice recognition, and face-in-a-crowd scenarios. This algorithm is not based on the typical approaches employing eigenfaces, minutia, wavelets, or other models and transforms, but uses a specialized data processing algorithm to compare input biometric features against enrolled biometrics within a database. It is envisioned that this algorithm technology can be ported from a software-implemented demonstration to a field programmable gate array (FPGA) implementation for use as a general-purpose biometric recognition engine for commercial and-or military systems requiring high speed multimodal biometric fusion based human identification
