Towards non-cooperative iris recognition systems
Iris Technology has been successfully applied to person verification and identification. However, all commercial products require user cooperation for iris image capture. This paper examines the new challenges of iris recognition when extended to less cooperative situations. With the current stress on security and surveillance, this has been an important consideration. First, a summary of research findings of the past decade on iris recognition is described Then we identified new challenges that will be encountered when extending these methods to less cooperative situations. The difficulties are great and this paper describes some initial work into this area. One difficulty studied is the loss of iris details captured. We propose a modified Kolmogorov complexity measure based on maximum Shannon entropy of wavelet packet reconstruction to quantify the iris information. Real-time eye-corner tracking, iris segmentation and feature extraction algorithms are implemented. Video images of the iris are captured by an ordinary CCD camera with a zoom lens. Experiments are performed and the performances and analysis of iris code method and correlation method are described. Several useful findings were reached albeit from a small database. The iris codes were found to contain almost all the discriminating information. Our correlation approach coupled with nearest neighbour classification outperforms the conventional thresholding method for iris recognition with degraded images.