CASIA-Iris-Africa:A Large-scale African Iris Image Database
作者机构：School of Artificial IntelligenceUniversity of Chinese Academy of SciencesBeijing 100049China Center for Research on Intelligent Perception and ComputingNational Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China
出 版 物：《Machine Intelligence Research》 (机器智能研究（英文版）)
年 卷 期：2024年第21卷第2期
页 面：383-399页
核心收录：
学科分类：08[工学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 081202[工学-计算机软件与理论]
基 金：国家自然科学基金 Strategic Priority Research Program of Chinese Academy of Sciences the CAS-TWAS president's Fellowship for International Doctoral Students sponsored by The Beijing Nova Program
主 题：African iris recognition racial bias iris image database biometrics iris recognition
摘 要：Iris biometrics is a phenotypic biometric trait that has proven to be agnostic to human natural physiological changes.Research on iris biometrics has progressed tremendously,partly due to publicly available iris databases.Various databases have been available to researchers that address pressing iris biometric challenges such as constraint,mobile,multispectral,synthetics,long-distance,contact lenses,liveness detection,etc.However,these databases mostly contain subjects of Caucasian and Asian docents with very few Africans.Despite many investigative studies on racial bias in face biometrics,very few studies on iris biometrics have been published,mainly due to the lack of racially diverse large-scale databases containing sufficient iris samples of Africans in the public domain.Furthermore,most of these databases contain a relatively small number of subjects and labelled images.This paper proposes a large-scale African database named Chinese Academy of Sciences Institute of Automation(CASIA)-Iris-Africa that can be used as a complementary database for the iris recognition community to mediate the effect of racial biases on Africans.The database contains 28717 images of 1023 African subjects(2046 iris classes)with age,gender,and ethnicity attributes that can be useful in demographically sensitive studies of Africans.Sets of specific application protocols are incorporated with the database to ensure the database’s variability and scalability.Performance results of some open-source state-of-the-art(SOTA)algorithms on the database are presented,which will serve as baseline performances.The relatively poor performances of the baseline algorithms on the proposed database despite better performance on other databases prove that racial biases exist in these iris recognition algorithms.
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