1 research outputs found
Ocular Recognition Databases and Competitions: A Survey
The use of the iris and periocular region as biometric traits has been
extensively investigated, mainly due to the singularity of the iris features
and the use of the periocular region when the image resolution is not
sufficient to extract iris information. In addition to providing information
about an individual's identity, features extracted from these traits can also
be explored to obtain other information such as the individual's gender, the
influence of drug use, the use of contact lenses, spoofing, among others. This
work presents a survey of the databases created for ocular recognition,
detailing their protocols and how their images were acquired. We also describe
and discuss the most popular ocular recognition competitions (contests),
highlighting the submitted algorithms that achieved the best results using only
iris trait and also fusing iris and periocular region information. Finally, we
describe some relevant works applying deep learning techniques to ocular
recognition and point out new challenges and future directions. Considering
that there are a large number of ocular databases, and each one is usually
designed for a specific problem, we believe this survey can provide a broad
overview of the challenges in ocular biometrics