Improvement of preprocessing method on fingerprint identification system by layered neural networks

Summary form only given, as follows. We constructed an individual identification system of fingerprints by three-layered neural networks, and investigated the effects of the preprocessing method for determining the centers of fingerprint images and the neural networks on the performance of an individual identification system. The fingerprint images were classified into four directions, 0°, 45°, 90° and 135°, then two kinds of smoothing were done and the neural networks were optimized. From the results, we found that the preprocessing and the layered neural networks were useful for the individual identification system with a high performance and that the preprocessing method determining the centers of fingerprint images produced higher performance than the system without the preprocessing.