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Iris recognition is a well-known biometric technique. The iris recognition is a kind of the biometrics technologies based on the physiological characteristics of human body, compared with the feature recognition based on the fingerprint, palm-print, face and sound etc, the iris has some advantages such as uniqueness, stability, high recognition rate, and non-infringing etc. Iris recognition, which is divided into four steps: segmentation, normalization, feature extraction and matching. The authors had taken iris images from database CASIA V4. They use Daugman's method using integro-differential operator for segmentation & the feature extraction algorithm based on Principle Component Analysis (PCA) & Independent Component Analysis (ICA) for a compact iris code. They use these methods to generate optimal basis elements which could represent iris signals efficiently.
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