Non-frontal/non-ideal Iris localization and acquisition

Iris and face biometric systems are under intense study as a multimodal pair due in part to the ability to acquire both with the same capture system. While several successful research efforts have considered facial imagesas part of an iris-face multimodal biometric system, there is little work in the area exploring the iris recognition problem under different poses of the subjects. This is due to the fact that most commercial iris recognition systems depend on the high performance algorithm patented by Daugman, which does not take into consideration the pose and illumination variations in iris acquisition. Hence there is an impending need for sophisticated iris detection systems that localize the iris region for different poses and different facial views. In this paper we present a non-frontal/non-ideal iris acquisition technique where iris images are extracted out of regular visual video sequences. This video sequence is captured 3 feet around the subject in a 90-degree arc from the profile view to the frontal view. We present a novel design for an iris detection filter that detects the location of the iris, the pupil and the sclera using a Laplacian of Gaussian ellipse detection technique. Experimental results show that the proposed approach can localize the iris location in facial images for a wide range of pose variations including semi-frontal views.