Iris recognition system based on video for unconstrained environments

Abstract

This paper proposes an iris image quality and segmentation accuracy evaluation method for videobased iris recognition systems, operating in unconstrained environment. Proposed approach consists of two stages of video quality evaluation that allows improving the iris recognition rates in non-ideal or no cooperative situations; where the first stage discards the low quality eye frames, while the second stage discards frames with low quality iris segmentation providing properly segmented iris frames to carry out the unconstrained iris recognition task. Although proposed scheme was evaluated using the Daugman algorithm, it may be used with several other iris recognition systems operating in constrained environments. Evaluation results show that the performance of conventional iris recognition system, using the proposed scheme, reduces the equal error rate (EER) value in about 12.2%.

Video Images Fusion to Improve Iris Recognition Accuracy in Unconstrained Environments

“…Thus, with the aim of overcoming these drawbacks, news approaches are being developed in an attempt to improve iris recognition performance under non ideal situations. Among these approaches, the video-based eye image acquisition for iris recognition seems to be an interesting alternative [5][6][7] because it can provide more information through the capture of a video iris sequences. Besides that, it is a friendly system because it is not intrusive and requires few users' cooperation.…”