The human iris is used for human recognition in various applications. However, deployment of iris recognition in forensic applications has not been reported. A primary reason is the lack of human-friendly techniques for iris comparison. The usage of iris recognition can be increased by visualizing the similarity between irises. Scientist Shen proposed the human-in-the-loop method for detecting and matching iris crypts. Thus with the help of this, we proposed a new approach for automatic detection and matching of crypts. This detection method is able to capture iris crypts of various sizes. This matching scheme is designed to handle potential topological changes in the detection of the same crypt in different images. In particular, this approach achieves over 22% higher rank one hit rate in the identification, and over 51% lower equal error rate in verification. In addition, the benefit of this approach on Multi-enrollment is experimentally demonstrated.