The Optimal Matching Algorithm for Multi-Scale Iris Recognition

As one of the most effective ways in biometrics, Iris Identification has drawn more and more attention in recognition technology. Fruitful achievement, both theoretically and practically, have been made and widely applied to various fields and industries. However, iris identification is easily affected by noises such as eyelashes, eyelids, sampling flares, and its quality and speed in actual practice is not so effective. We analyses the general approach based on the extraction and matching of feature code, and then design an new iris identification algorithm based on multi-scale gray matching. It proposes a standardized solution for the noise integration of using in login and sample iris images, and uses directly surface match way to judge recognition.With the method, we can extract more junior primitive iris data, analyses and process them, and increase area used to iris identification, reduce residual caused by the no unified available area. The results show that the algorithm has virtues of both accuracy and speed, and has some applicated fields.