A Novel Similarity Measurement for Iris Authentication
Mohamed Mostafa Abd Allah · 2013
This paper introduces a novel similarity measuremen t which derives the likelihood ratio between two eyes. The proposed method takes into consideration the individual and system error rates of eye features. It handles two kinds of individual probab ilities: (consistent Probability (CP), the Inconsis tent Probability (IP),) to achieve the best matching app roach between two feature sets. While calculating t he probabilities, we assume that a reasonable alignmen t approach should be obtained before the matching approach introduced. The proposed matching algorith m is theoretically proved to be optimal, and experimental results show that the proposed method has more efficient performance on separating genuine and impostor pairs Povzetek: Predstavljena je nova metoda za prepoznav anje identitete o ces.