Iris imaging in visible spectrum using white LED

Iris recognition in the visible spectrum has many challenging aspects. Especially, for subjects with dark iris color, which is caused by higher melanin pigmentation and collagen fibrils, the pattern is not clearly observable under visible light. Thus, the verification performance is generally lowered due to limited texture visibility in the captured iris samples. In this work, we propose a novel method of employing a white light-emitting-diode (LED) to obtain high-quality iris images with detailed texture. To evaluate the proposed set-up with LED light, we have acquired a new database of dark iris images comprising of 62 unique iris instances with ten samples each that were captured in different sessions. The database is acquired using three different smartphones - iPhone 5S, Nokia Lumia 1020 and Samsung Active S4. We also provide a benchmark of the proposed method with conventional to Near-Infra-Red (NIR) images, which are available for a subset of the database. Extensive experiments were carried out using five different well-established iris recognition algorithms and one commercial-of-the-shelf algorithm. They demonstrate the reliable performance of the proposed image capturing setup with GMR of 91.01% at FMR = 0.01% indicating the applicability in real-life authentication scenarios.