An efficient process of recognition of human iris based on contourlet transforms

Iris recognition a new biometric technology has great advantages such as variability, stability and security. In this paper we propose a feature extraction method for iris recognition based on contourlet transform. Contourlet transform captures the intrinsic geometrical structures of iris image. It decomposes the iris image into a set of directional subbands with texture details captured in different orientations at various scales. Discriminant analysis is used to determine the optimal threshold for the selection of dominant directional energy components. Only dominant directional energy components are employed as elements of the input feature vector. These input feature vectors are compared with the template feature vectors. Experimental results show that the proposed method reduce processing time and increase the classification accuracy and outperforms the wavelet based method.