AMO - Advanced Modeling and Optimization, Volume 9, Number 2, 2007
نویسندگان
چکیده
Iris recognition a new biometric technology has great advantages such as variability, stability and security. In this paper we propose a new 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.
منابع مشابه
AMO-Advanced Modeling and Optimization, Volume 9, Number 1, 2007, pp.37-51 Quadratic Pareto Optimal Control For Boundary Infinite Order Parabolic Equation With State-Control Constraints
A boundary Pareto optimal control problem for the parabolic operator with infinite order is considered. The performance index has an integral form. Constraints on controls and on states are imposed. To obtain optimality conditions for the Neumann problem, the generalization of the Dubovitskii-Milyutin Theorem given by Walczak in Refs.[33,34], was applied. AMS Subject Classification : 35K20, 49J...
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