Cross-spectral Iris Recognition for Mobile Applications using High-quality Color Images
This addresses biometric authentication for mobile applications, but it is incremental as it builds on existing cross-spectral methods with a specific scenario.
The paper tackled cross-spectral iris recognition by using high-quality color images from mobile phones against near-infrared enrollment images, showing that selective RGB channel conversion based on iris coloration improves accuracy, reducing equal error rates to as low as 2% in some cases.
With the recent shift towards mobile computing, new challenges for biometric authentication appear on the horizon. This paper provides a comprehensive study of cross-spectral iris recognition in a scenario, in which high quality color images obtained with a mobile phone are used against enrollment images collected in typical, near-infrared setups. Grayscale conversion of the color images that employs selective RGB channel choice depending on the iris coloration is shown to improve the recognition accuracy for some combinations of eye colors and matching software, when compared to using the red channel only, with equal error rates driven down to as low as 2%. The authors are not aware of any other paper focusing on cross-spectral iris recognition is a scenario with near-infrared enrollment using a professional iris recognition setup and then a mobile-based verification employing color images.