A Novel Embedded Fingerprints Authentication System Based on Singularity Points

In this paper a novel embedded fingerprints authentication system based on core and delta singularity points detection is proposed. Typical fingerprint recognition systems use core and delta singularity points for classification tasks. On the other hand, the available optical and photoelectric sensors give high quality fingerprint images with well defined core and delta points, if they are present. In the proposed system, fingerprint matching is based on singularity points position, orientation, and relative distance detection. As result, fingerprint matching involves the comparison between few features leading to a very fast system with recognition rates comparable to the standard minutiae based recognition systems. The whole system has been prototyped on the Celoxica RC203E board, equipped with a Xilinx VirtexII FPGA. The prototype has been tested with the FVC databases. Hardware system performance show high recognition rates and low execution time: FAR = 1.2% and FRR=2.6%, while each fingerprint elaboration requires 34.82 ms. Considering both FAR, FRR indexes and the high speed, the proposed system could be used for identification tasks in large fingerprint databases. To the best of our knowledge, this is the first authentication system based on singularity points.