Iris features extraction using dual-tree complex wavelet transform

This paper presents an iris recognition method based on the two dimensional dual-tree complex wavelet transform (2D-CWT) and the support vector machines (SVM). 2D-CWT has such significant properties as the approximate shift-invariance, high directional selectivity and computationally much more efficient. These properties are very useful in invariant iris recognition. SVM is used as a classifier and several kernel functions are tested in the experiments. The obtained experimental results showed that the proposed approach enhanced the classification accuracy. The experimental results were also compared with the k-NN and Naïve Bayes classifiers to demonstrate the efficacy of the proposed technique.