Abstract:

In view of the limitation of poor direction selectivity about wavelet transform and iris image having rich texture features, an iris feature extraction method  based on contourlet transform for obtaining high quality features is proposed in the paper. First of all, the preprocessed iris image is decomposed by contourlet, then, according to the information that high and low frequency subbands represent, it adopts different extraction ways, both the mean and variance of low frequency subband coefficients and the energy of high frequency subband coefficients are extracted to be the feature vectors. Finally, it carries the test on CASIA Ver1.0 and MMU iris databases with SVMs and Hamming distances. Compared with the feature extraction method  based on the  Harr wavelet and discrete cosine transform, the proposed method can achieve better performance.

Key words: feature extraction;contourlet transform;iris recognition;subband energy