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Periocular recognition has gained significant importance with the increasing use of surgical masks to safeguard against environmental pollution or for improving accuracy of iris recognition. This paper proposes a new framework for accurately matching cross-spectral periocular images using Markov random fields (MRF) and three patch local binary patterns (TPLBP). We study the problem of cross-spectral...
Automated human identification at-a-distance, using completely automated iris segmentation, is highly challenging and has wide range of civilian and forensics applications. Iris images acquired at-a-distance using visible and infrared imaging are often noisy and suffer from divergent spectral changes largely resulting from scattering, albedo and spectral absorbance selectivity. Therefore further research...
Iris recognition from at-a-distance face images has high applications in wide range of applications such as remote surveillance and for civilian identification. This paper presents a completely automated joint iris and periocular recognition approach from the face images acquired at-a-distance. Each of the acquired face images are used to detect and segment periocular images which are then employed...
This paper presents two new approaches to improve the performance of palm-vein-based identification systems presented in the literature. The proposed approach attempts to more effectively accommodate the potential deformations, rotational and translational changes by encoding the orientation preserving features and utilizing a novel region-based matching scheme. We systematically compare the previously...
This paper investigates some promising approaches for the automated personal identification using contactless palmvein imaging. We firstly present two new palmvein representations, using Hessian phase information from the enhanced vascular patterns in the normalized images and secondly from the orientation encoding of palmvein line-like patterns using localized Radon transform. The comparison and...
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