Novel system for human iris recognition depending on morphological operations and MLP classifiers
Abstract
This article suggested a novel system for human iris recognition, and created two algorithms for constrained iris images segmentation. We used Casia-Iris-Syn database Supplied by National Laboratory for Pattern Recognition , Institute of Automation , Chinese Academy of Sciences. K-fold cross validation method, morphological operations and multi-layer perceptron neural networks were used in this system. Two novel approaches has been proposed in the iris recognition system; the first was generated for iris image segmentation with an overall accuracy rate of (99.72%) for (10,000) iris images taken from the casia-iris-syn database, and the second was designed for feature extraction phase with average recognition rate of (99.78% for training patterns and 85.32% for testing patterns) using the same database. . We recommended the suggested method as an excellent system for human iris recognition.
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