Publications:Eigen-patch iris super-resolution for iris recognition improvement


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Title Eigen-patch iris super-resolution for iris recognition improvement
Author Fernando Alonso-Fernandez and Reuben A. Farrugia and Josef Bigun
Year 2015
PublicationType Conference Paper
HostPublication 2015 23rd European Signal Processing Conference (EUSIPCO)
Conference 23rd European Signal Processing Conference, EUSIPCO, Nice, France, 31 August–4 September, 2015
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Abstract Low image resolution will be a predominant factor in iris recognition systems as they evolve towards more relaxed acquisition conditions. Here, we propose a super-resolution technique to enhance iris images based on Principal Component Analysis (PCA) Eigen-transformation of local image patches. Each patch is reconstructed separately, allowing better quality of enhanced images by preserving local information and reducing artifacts. We validate the system used a database of 1,872 near-infrared iris images. Results show the superiority of the presented approach over bilinear or bicubic interpolation, with the eigen-patch method being more resilient to image resolution reduction. We also perform recognition experiments with an iris matcher based 1D Log-Gabor, demonstrating that verification rates degrades more rapidly with bilinear or bicubic interpolation. ©2015 IEEE