A contourlet transform based for features fusion in retina and iris multimodal biometric system

Abstract

Fusion biometric modal contributes in two aspects. It can not only improve the biometric recognition accuracy, but also gives a comparatively safe strategy, since it is difficult for intruders to achieve multi-biometric information simultaneously, especially the iris information. The contourlet transform is a new two-dimensional extension of the wavelet transform using multiscale and directional filter banks. The contourlet expansion is composed of basis images oriented at various directions in multiple scales, with flexible aspect ratios. In this paper, by using Contourlet transform, we extract the features of retina and iris, and fuse them at feature level and utilize Hamming distance for matching purpose to provide a higher accuracy than unimodal system. The experimental results show that our biometric system based on the integration of retina and iris traits achieve an EER= 0.0413%.