Date of Publication :14th December 2016
Abstract: Among various methods of personal identification iris recognition is regarded as the most reliable and accurate system available. The purpose of this paper is to represent iris recognition algorithm so as to prove its reliability as a biometric on the basis of its performance. The images selected for study are from CASIA iris database. The classification is done on the basis of the most repeatedly occurring class using KNN classifier. Euclidian distance metric was employed to check the similarity between two iris images and the two images said to be matched if its value is less than or equal to threshold. The system was tested and shown an overall accuracy of 97.5 % with false rejection rate of 3% and false acceptance rate of 2%.
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