Iris recognition is the method of recognizing individuals based on their iris pattern. Iris of the human eye is the annular region between the pupil and sclera, and controls the amount of incident light on retina.
Unlike the PCs and laptops, the smartphone is a very personal device, where users store their personal data, passwords, health information, financial transactions, daily calendars and to do list and much more. Hence, secure authentication of a smartphone user’s identity is crucial. The objective of this work is to provide a practical iris recognition solution for user authentication in next generation smartphones.
For smartphones, a typical use case is the user authentication while holding the device at a comfortable arm’s length (approximately 15-30cm from face) as in Figure 1.
The key element for acquiring high quality iris images is the imaging system. A dedicated iris acquisition system is needed to provide a working solution based on the technology available in today’s smartphones. The key design question is whether to use two different front facing cameras (one for general purpose applications such as video call and a second one dedicated for iris recognition) or a hybrid camera which can be used for both iris recognition and other general use cases. These options are depicted in Figure 2.
Our proof-of-concept hybrid RGB/NIR camera for smartphone iris recognition is shown in Figure 4
As the use of iris biometrics on smartphone devices becomes more widely adopted, it is to be expected that there will be similar efforts in the research community to beat the biometric by exploring new spoofing methods. Hence, simple, cost-effective yet powerful liveness detection should be incorporated on smartphones. Such a technique ideally should not require any additional hardware or user interaction and should be computationally light enough to be embedded in the smartphone camera pipeline or dedicated iris recognition digital signal processors.
Such a solution is presented in Figure 5.
Iris obfuscation in digital images can be a potential solution to some of the privacy concerns which may arise with the wider adoption of iris recognition. Iris pattern obfuscation aims to detect the iris region in the images and replace it in a way that the replaced images will look natural and similar to the subject’s original eye, but the iris information should not match to that of the original iris. This prevent the possibility of using iris images from a personal photograph for spoofing attacks on iris recognition systems.
Examples of iris pattern obfuscation is shown in Figure 6.
A detailed overview can be found here:
The full description can be found here: