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
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.