随着身份认证需求增长,适用于多领域的虹膜识别技术因高准确性成为研究重点。本研究设计了高精度虹膜识别镜头,由四片透镜组成,总长4.00 mm, F#2.4,采用Optic Studio ZEMAX软件仿真。仿真结果显示,镜头MTF在关键频率下大于0.6,畸变小于0...随着身份认证需求增长,适用于多领域的虹膜识别技术因高准确性成为研究重点。本研究设计了高精度虹膜识别镜头,由四片透镜组成,总长4.00 mm, F#2.4,采用Optic Studio ZEMAX软件仿真。仿真结果显示,镜头MTF在关键频率下大于0.6,畸变小于0.6%,相对照度稳定。该设计满足虹膜识别高精度要求,同时结合教学实践,提升了学生光学设计与工程能力。此研究为虹膜识别镜头开发提供了参考,也为案例教学奠定了基础。展开更多
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 datab...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.展开更多
文摘随着身份认证需求增长,适用于多领域的虹膜识别技术因高准确性成为研究重点。本研究设计了高精度虹膜识别镜头,由四片透镜组成,总长4.00 mm, F#2.4,采用Optic Studio ZEMAX软件仿真。仿真结果显示,镜头MTF在关键频率下大于0.6,畸变小于0.6%,相对照度稳定。该设计满足虹膜识别高精度要求,同时结合教学实践,提升了学生光学设计与工程能力。此研究为虹膜识别镜头开发提供了参考,也为案例教学奠定了基础。
文摘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.
