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• W2597477065 abstract "A biometric system provides automatic identification of an individual based on unique features or characteristics possessed by that person. Iris recognition is regarded as one of the most reliable and accurate biometric systems available. This paper, proposes an efficient iris recognition system that employs a novel method to localize the iris region in the eye image based on approximating the iris radius using the pupil characteristics and cumulative SUM based gray change analysis to extract features from the normalized iris template and also Fuzzy ARTMAP neural network to classify the iris codes. The results of simulations on a set of 756 eye images illustrate that a fast, accurate and noise resistant personal identification system has been successfully designed. The proposed system achieved 0 false acceptance rate using 1800-bit binary iris codes and recognized all authorized users with 100% accuracy." @default.
• W2597477065 created "2017-04-07" @default.
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• W2597477065 date "2013-01-01" @default.
• W2597477065 modified "2023-09-27" @default.
• W2597477065 title "Iris Recognition using a Novel Segmentation Method and Fuzzy ARTMAP Neural Network" @default.
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