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Fusion of Hybrid Domain features for Iris

The Biometric systems are used for personal authentication. Iris based Biometric systems are more efficient compared to the systems based on other Biometric traits. In this paper, Fusion of Hybrid Domain features for Iris Recognition (FHDIR) is proposed. The CASIA Iris database is considered for the performance analysis. The preprocessing step includes resizing, binarization, cropping and splitting the Iris image into left half and right half. The Fast Fourier Transform (FFT) is applied on the left portion of the Iris to generate absolute value of FFT coefficients. The Principal Component Analysis (PCA) is applied on right portion of Iris to generate Eigen vectors. The FFT and PCA coefficients are fused using arithmetic addition to generate final feature vector set. The test Iris features are compared with the database feature set using Euclidean Distance to identify persons. It is observed that the performance parameters such as FRR, FAR and TSR values are better in the case of proposed algorithm compared to the existing algorithms. Keywords— Iris Recognition; PCA; FFT; TSR; Euclidean Distance;