Title: Anti-spoofing: Iris Databases
Publisher: Springer US
Publication Year: 2014
JRC N°: JRC86074
ISBN: 978-3-642-27733-7
URI: http://link.springer.com/referenceworkentry/10.1007/978-3-642-27733-7_9050-2
DOI: 10.1007/978-3-642-27733-7_9050-2
Type: Articles in periodicals and books
Abstract: Anti-spoofing may be defined as the pattern recognition problem of automatically differentiating between real and fake biometric samples produced with a synthetically manufactured artefact (e.g., iris photograph or plastic eye). As in any other machine learning problem the availability of data is a critical factor to be able to successfully address this challenging task. Furthermore, these data should be public, so that the performance of different protection methods may be compared in a fully fair manner. The present entry describes general concepts regarding spoofing dataset acquisition and particularizes them to the field of iris recognition. It also gives a summary of the most important features of the current publicly available iris spoofing databases.
JRC Directorate:Space, Security and Migration

Files in This Item:
There are no files associated with this item.

Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.