Matching iris images against face images using a joint dictionary-based sparse representation scheme
Raghavender Reddy Jillela, Arun A. Ross · Institution of Engineering and Technology eBooks · 2017
In this chapter, the problem of matching face against iris images using ocular information is considered. Face and iris images are typically acquired using different sensors: face recognition is predominantly conducted in the visible (VIS) spectrum while iris recognition is performed in the near-infrared (NIR) spectrum. Further, the subject-to-camera distance for face and iris recognition is substantially different. Due to these and other factors, the problem of matching face images against iris images is riddled with several challenges. To address this, we propose a novel matching algorithm based on Joint Dictionary-based Sparse Representation (JDSR) that exploits the use of ocular information available in both face and iris images. Experimental results on a database containing 1,358 images of 704 subjects indicate that the ocular region can provide better performance than the iris region in this challenging cross-modality matching scenario.