Abstract: This paper proposes an automated system for recognizing palmprints for biometric identification of individuals. Palmprint images are converted to the frequency domain using 2D DFT and thereafter bandpass filtered using a log-Gabor filter to extract the phase symmetry information. Classification is done on basis of correlation between training and testing set images. The approach is tested over a data set of 200 images divided into 10 classes and seen to provide 100% recognition accuracy. A contemporary technique is also implemented on the current dataset for comparison of accuracy results.