Iris Recognition Based on a Novel Normalization Method and Contourlet Transform

We proposed a new normalization method for iris recognition, which is different from the conventional one in which the annular iris region is unwrapped to a rectangular block under polar coordinate. In this method, we investigate the effect of interpolation and decimation in conventional normalization method to recognition rate for the first time. We used the original texture to fill the pupil area, then a novel normalized image can be obtained with the geometric structure and directional information of original iris image well preserved, which enables us to choose simpler features than before. Subsequently, we extracted the multi-direction and multi-scale information feature of normalized iris image by contourlet transform, and adopt SVM to classify the features. Experimental results validate the improvement of recognition rate.