Iris Recognition based on Machine Learning Techniques

Abstract

Biometrics is a discipline that studies methods for verification and identification of individuals based on physical or behavioral characteristics of a person. The iris of the human eye is a structure which can be used as a reliable feature to identify individuals since its intrinsic pattern is considered unique and permanent for each individual. In this project, an iris recognition system is proposed based on speeded up robust features (SURF) matching statistics which feed a learning algorithm to automatically decide whether the two images correspond to the same iris. Experiments performed on CASIA iris image database show that our method has promising capabilities for iris recognition.

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