Аннотация:We present the use of phase-only filter-based correlation for fingerprint pattern identification. The main advantage of this approach is that it is distortion tolerant and can be realized in optical or electronic parallel hardware. Given that real-world fingerprints are almost never perfect, distortion tolerance can prove to be very important for this application. Our results indicate that the algorithm can identify prints with 58% of the data missing on average. With large fingerprint databases, identification can be a computationally challenging task. The high parallelism in the phase-only correlation filter makes it ideally suited to field programmable gate array (FPGA)-based hardware acceleration. We examine the FPGA-based acceleration of the fingerprint algorithm. On a Xilinx Virtex II Pro FPGA, we achieve speedups of about 47 times over an optimized C implementation of the algorithm on a 2.2-GHz AMD Opteron processor. Our FPGA implementation is optimized to allow efficient processing of large databases.
