An effective human iris code with low complexity

A human iris coding technique is reported based upon differences in the power spectrum of fragments from normalized iris images. The procedure has been applied to a set of 2174 images from 308 eyes and tuned over a range of parameters. For identity recognition, 100% correct recognition is achieved using a weighted Hamming distance metric. For identity verification, a variable threshold is applied to the distance metric and the false acceptance and false rejection rates are recorded. After tuning the various parameters, the method achieves the lowest false acceptance rate at the point of first false rejection amongst the three algorithms tested, as well as the lowest complexity.