Research on human eye image processing and iris recognition has grown steadily over the last few decades. It is important for researchers interested in this discipline to know the relevant datasets in this area to (i) be able to compare their results and (ii) speed up their research using existing datasets rather than creating custom datasets. In this paper, we provide a comprehensive overview of the existing publicly available datasets and their popularity in the research community using a bibliometric approach. We reviewed 158 different iris datasets referenced from the 689 most relevant research articles indexed by the Web of Science online library. We categorized the datasets and described the properties important for performing relevant research. We provide an overview of the databases per category to help investigators conducting research in the domain of iris recognition to identify relevant datasets.
Omelina, L , Goga, J, Pavlovicova, J, Oravec, M & Jansen, B 2021, ' A survey of iris datasets ', Image and Vision Computing , vol. 108, 104109, pp. 1-20.
Omelina, L. , Goga, J., Pavlovicova, J., Oravec, M. , & Jansen, B. (2021). A survey of iris datasets . Image and Vision Computing , 108 , 1-20. [104109].
@article{f75b953acc804aeb89feea05a203a72e,
title = " A survey of iris datasets " ,
abstract = " Research on human eye image processing and iris recognition has grown steadily over the last few decades. It is important for researchers interested in this discipline to know the relevant datasets in this area to (i) be able to compare their results and (ii) speed up their research using existing datasets rather than creating custom datasets. In this paper, we provide a comprehensive overview of the existing publicly available datasets and their popularity in the research community using a bibliometric approach. We reviewed 158 different iris datasets referenced from the 689 most relevant research articles indexed by the Web of Science online library. We categorized the datasets and described the properties important for performing relevant research. We provide an overview of the databases per category to help investigators conducting research in the domain of iris recognition to identify relevant datasets. " ,
keywords = " Biometrics, Iris recognition, Iris datasets, Human iris " ,
author = " Lubos Omelina and Jozef Goga and Jarmila Pavlovicova and Milos Oravec and Bart Jansen " ,
note = " Funding Information: The research described in the paper was done within the project No. 1/0867/17 of the Slovak Grant Agency VEGA. Publisher Copyright: { extcopyright} 2021 The Authors Copyright: Copyright 2021 Elsevier B.V., All rights reserved. " ,
year = " 2021 " ,
month = apr,
doi = " 10.1016/j.imavis.2021.104109 " ,
language = " English " ,
volume = " 108 " ,
pages = " 120 " ,
journal = " Image and Vision Computing " ,
issn = " 0262-8856 " ,
publisher = " Elsevier Limited " ,
}