Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/23938
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Alonso-Fernandez, Fernando | - |
dc.contributor.author | Farrugia, Reuben A. | - |
dc.contributor.author | Bigun, Josef | - |
dc.date.accessioned | 2017-11-16T11:19:29Z | - |
dc.date.available | 2017-11-16T11:19:29Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Alonso-Fernandez, F., Farrugia, R., & Bigun, J. (2015). Eigen-patch iris super-resolution for iris recognition improvement. 23rd European Signal Processing Conference (EUSIPCO), Nice. 76-80. | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/23938 | - |
dc.description.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. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_GB |
dc.rights | info:eu-repo/semantics/openAccess | en_GB |
dc.subject | High resolution imaging | en_GB |
dc.subject | Principal components analysis | en_GB |
dc.subject | Machine learning | en_GB |
dc.subject | Optical pattern recognition | en_GB |
dc.subject | Biometric identification -- Technological innovation | en_GB |
dc.subject | Pattern recognition systems | en_GB |
dc.title | Eigen-patch iris super-resolution for iris recognition improvement | en_GB |
dc.type | conferenceObject | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.bibliographicCitation.conferencename | 23rd European Signal Processing Conference (EUSIPCO) | en_GB |
dc.bibliographicCitation.conferenceplace | Nice, France, 31/08/-04/09/2015 | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
dc.identifier.doi | 10.1109/EUSIPCO.2015.7362348 | - |
Appears in Collections: | Scholarly Works - FacICTCCE |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
OA111 (5).pdf | 318.91 kB | Adobe PDF | View/Open |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.