Iris Recognition Based on Human-Interpretable Features

The iris is a stable biometric that has been widely used for human recognition in various applications. However, official deployment of the iris in forensics has not been reported. One of the main reasons is that the current iris recognition techniques in hard to visually inspect by examiners. To further promote the maturity of iris recognition in forensics, one way is to make the similarity between irises visualizable and interpretable. Recently, a human-in-the-loop iris recognition system was developed, based on detecting and matching iris crypts. Building on this framework, we propose a new approach for detecting and matching iris crypts automatically. Our detection method is able to capture iris crypts of various sizes. Our matching scheme is designed to handle potential topological changes in the detection of the same crypt in different acquisitions. Our approach outperforms the known visible feature based iris recognition method on two different datasets, by over 19 % higher rank one hit rate in identification and over 46 % lower equal error rate in verification.