Personal Identification with Human Iris Recognition Based on EMD

Iris recognition is an invasive biometric technique used to identify human being. Iris is defined as annular region between pupil and sclera of human eye which exhibits extraordinary texture that is unique for each individual. Hence, imposes various challenges in accurate iris segmentation and feature extraction techniques to provide many opportunities for researchers in pursuing their research work in this area. The iris is a stable biometric trait that has been widely 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. To further promote the use of iris recognition in forensics, the similarity between irises should be made visualizable and interpretable. Building on this framework, we propose a new approach for detecting and matching iris for personal identification process. we adopt a matching model based on the Earth Mover's Distance (EMD). Our approach outperforms the known visible-feature-based iris recognition method on three different data sets. In particular, our approach achieves over 22% higher rank one hit rate in identification, and over 51% lower equal error rate in verification. In addition, the benefit of our approach on multi-enrollment is experimentally demonstrated.