Fusing iris and periocular information for cross-sensor recognition

• Announcement of an iris and periocular dataset, with 10 different mobile setups.
• Mobile biometric recognition approach based on iris and periocular information.
• Improvements from a sensor-specific color calibration technique are reported.
• Biometric recognition feasibility over mobile cross-sensor setups is shown.
• Preferable mobile setups are pointed out.

In recent years, the usage of mobile devices has increased substantially, as have their capabilities and applications. Extending biometric technologies to these gadgets is desirable because it would facilitate biometric recognition almost anytime, anywhere, and by anyone. The present study focuses on biometric recognition in mobile environments using iris and periocular information as the main traits. Our study makes three main contributions, as follows. (1) We demonstrate the utility of an iris and periocular dataset, which contains images acquired with 10 different mobile setups and the corresponding iris segmentation data. This dataset allows us to evaluate iris segmentation and recognition methods, as well as periocular recognition techniques. (2) We report the outcomes of device-specific calibration techniques that compensate for the different color perceptions inherent in each setup. (3) We propose the application of well-known iris and periocular recognition strategies based on classical encoding and matching techniques, as well as demonstrating how they can be combined to overcome the issues associated with mobile environments.