Palmprint identification using Gabor wavelet probabilistic neural networks

In this paper, a novel algorithm for automatic palmprint identification based on Gabor wavelet probabilistic neural networks (GWPNN) is proposed, which incorporating advantages of Gabor wavelet network (GWN) and probabilistic neural networks (PNN). We first construct a GWN model for each individual palmprint and then combine it with PNN in a unified framework that aims to significantly improve the discriminant capability for palmprint recognition. In our experiments, the accuracy identification rate can reach 99.5% on the database that contains 1,971 image samples. It demonstrates that proposed algorithm is effective and robust.