Palmprint classification using contourlets

Abstract

In this paper, we propose a new palmprint classification method by using the contourlet features. The contourlet transform is a new two dimensional extension of the wavelet transform using multiscale and directional filter banks. It can effectively capture smooth contours that are the dominant features in palmprint images. AdaBoost is used as a classifier in the experiments. Experimental results show that the contourlet features are very stable features for invariant palmprint classification, and better classification rates are reported when compared with other existing classification methods. ©2007 IEEE.