Double Layers Self-Organized Spiking Neural P Systems With Anti-Spikes for Fingerprint Recognition

Abstract

In this paper, we design a double layers self-organized spiking neural P system with anti-spikes for fingerprint recognition. The system can self-adaptively create and delete synapse between the neurons in different layers and recognize fingerprints by the spike trains emitted out of the output neurons. Data experiments are conducted on FVC2002 and FVC2004 Databases with EER (Equal Error Rate) 9.5% around, and much less parameters are involved in our SN P systems than Capsule Neural Networks. To our best knowledge, it is the first attempt of using SN P systems to do fingerprint recognition, which can also provide theoretical models for spiking neural circuits recognizing fingerprints.