A Palmprint Recognition System Based on Gabor Wigner Transform as Feature Extraction Technique

In the present paper, a palmprint recognition system has been proposed in which the recently proposed Gabor-Wigner transform (GWT) has been used to extract the features from the palmprint images. The novelty of the system lies in the fact that GWT has been used for the first time for feature extraction in a biometric system. A particle swarm optimization technique has been used to select the significant features and to reduce the dimension of the obtained feature vectors while keeping the same level of performance. The receiver operating characteristic (ROC) curve and the equal error rate (EER) have been used to evaluate the performance of the technique.