Abstract :
Iris became an important biometric in the last decade, due to its uniqueness and richness of features. In this paper, a novel super-resolution and image registration technique for visual (non-infra-red) iris images is presented. In the proposed technique, a full face, 3 second long, 90 frames, visual video is captured with a digital camera located 3 feet away from each subject. Iris images are segmented from the full face image. A cross correlation model is applied for the registration/ alignment of full gray scale iris images. A high resolution iris image, that is 4 times higher in terms of size and resolution, is constructed from every 9 low resolution images. This process of building a high resolution image is based on an auto_regressive signature model between consecutive low resolution images in filling the sub pixels in the constructed high resolution image. Then this process is iterated until a 16 times higher resolution iris image is constructed. Illustrative images are shown that prove the effectiveness of the proposed technique.
Keywords :
eye; image registration; image resolution; image segmentation; video signal processing; auto_regressive signature model; cross correlation model; digital camera; face image; image alignment; image registration technique; image segmentation; iris images; sub pixels; super-resolution construction; visual low resolution face video; Biometrics; Buildings; Digital cameras; Image recognition; Image registration; Image resolution; Image segmentation; Iris; Pixel; Videoconference;
