Abstract
In my thesis, we propose a new method named Dynamic Programming Based Matching Pursuit algorithm for iris-based personal identification. The method modifies the matching pursuit algorithm so that it selects the most representative path to do iris recognition. Our system consists of three parts: identification, verification and performance evaluation. The experimental results demonstrate the efficacy of the proposed method by showing that it attains a better ROC curve and faster speed than the conventional matching pursuit based iris recognition system.