NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization

Caiyong Wang; Yunlong Wang; Kunbo Zhang; Jawad Muhammad; Tianhao Lu; Qi Zhang; Qichuan Tian; Zhaofeng He; Zhenan Sun; Yiwen Zhang; Tianbao Liu; Wei Yang; Dongliang Wu; Yingfeng Liu; Ruiye Zhou; Huihai Wu; Hao Zhang; Junbao Wang; Jiayi Wang; Wantong Xiong; Xueyu Shi; Shao Zeng; Peihua Li; Haodong Sun; Jing Wang; Jiale Zhang; Qi Wang; Huijie Wu; Xinhui Zhang; Haiqing Li; Yu Chen; Liang Chen; Menghan Zhang; Ye Sun; Zhiyong Zhou; Fadi Boutros; Naser Damer; Arjan Kuijper; Juan Tapia; Andres Valenzuela; Christoph Busch; Gourav Gupta; Kiran Raja; Xi Wu; Xiaojie Li; Jingfu Yang; Hongyan Jing; Xin Wang; Bin Kong; Youbing Yin; Qi Song; Siwei Lyu; Shu Hu; Leon Premk; Matej Vitek; Vitomir Struc; Peter Peer; Jalil Nourmohammadi Khiarak; Farhang Jaryani; Samaneh Salehi Nasab; Seyed Naeim Moafinejad; Yasin Amini; Morteza Noshad

doi:10.1109/IJCB52358.2021.9484336

NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization

Caiyong Wang
, Yunlong Wang
, Kunbo Zhang
, Jawad Muhammad
, Tianhao Lu
, Qi Zhang
, Qichuan Tian
, Zhaofeng He
, Zhenan Sun
, Yiwen Zhang
, Tianbao Liu
, Wei Yang
, Dongliang Wu
, Yingfeng Liu
, Ruiye Zhou
, Huihai Wu
, Hao Zhang
, Junbao Wang
, Jiayi Wang
, Wantong Xiong

Xueyu Shi, Shao Zeng, Peihua Li, Haodong Sun, Jing Wang, Jiale Zhang, Qi Wang, Huijie Wu, Xinhui Zhang, Haiqing Li, Yu Chen, Liang Chen, Menghan Zhang, Ye Sun, Zhiyong Zhou, Fadi Boutros, Naser Damer, Arjan Kuijper, Juan Tapia, Andres Valenzuela, Christoph Busch, Gourav Gupta, Kiran Raja, Xi Wu, Xiaojie Li, Jingfu Yang, Hongyan Jing, Xin Wang, Bin Kong, Youbing Yin, Qi Song, Siwei Lyu, Shu Hu, Leon Premk, Matej Vitek, Vitomir Struc, Peter Peer, Jalil Nourmohammadi Khiarak, Farhang Jaryani, Samaneh Salehi Nasab, Seyed Naeim Moafinejad, Yasin Amini, Morteza Noshad

Department of Computer Science and Engineering

Beijing University of Civil Engineering and Architecture
CASIA
Chinese People's Public Security University
Northeastern University China
Dalian University of Technology
IriStar Technology Co. Ltd
Arak University
Beijing University of Posts and Telecommunications
Southern Medical University
Shanghai University of Electric Power
Xi'An Quanxiu Technology Co. Ltd
Jilin University
Fraunhofer Institute for Computer Graphics Research
Darmstadt University of Applied Sciences
Norwegian University of Science and Technology
Chengdu University of Information Technology
Keya Medical
SUNY Buffalo
University of Ljubljana
Warsaw University of Technology
Lorestan University
Shahid Beheshti University
Kharazmi University
Stanford University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

36 Scopus citations

Abstract

For iris recognition in non-cooperative environments, iris segmentation has been regarded as the first most important challenge still open to the biometric community, affecting all downstream tasks from normalization to recognition. In recent years, deep learning technologies have gained significant popularity among various computer vision tasks and also been introduced in iris biometrics, especially iris segmentation. To investigate recent developments and attract more interest of researchers in the iris segmentation method, we organized the 2021 NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization (NIR-ISL 2021) at the 2021 International Joint Conference on Biometrics (IJCB 2021). The challenge was used as a public platform to assess the performance of iris segmentation and localization methods on Asian and African NIR iris images captured in non-cooperative environments. The three best-performing entries achieved solid and satisfactory iris segmentation and localization results in most cases, and their code and models have been made publicly available for reproducibility research.

Original language	English
Title of host publication	Proceedings - 2021 International Joint Conference on Biometrics, IJCB 2079
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665437806
DOIs	https://doi.org/10.1109/IJCB52358.2021.9484336
State	Published - Aug 4 2021
Event	2021 IEEE International Joint Conference on Biometrics, IJCB 2021 - Shenzhen, China Duration: Aug 4 2021 → Aug 7 2021

Publication series

Name	2021 IEEE International Joint Conference on Biometrics, IJCB 2021

Conference

Conference	2021 IEEE International Joint Conference on Biometrics, IJCB 2021
Country/Territory	China
City	Shenzhen
Period	08/4/21 → 08/7/21

Access to Document

10.1109/IJCB52358.2021.9484336

Cite this

Wang, C., Wang, Y., Zhang, K., Muhammad, J., Lu, T., Zhang, Q., Tian, Q., He, Z., Sun, Z., Zhang, Y., Liu, T., Yang, W., Wu, D., Liu, Y., Zhou, R., Wu, H., Zhang, H., Wang, J., Wang, J., ... Noshad, M. (2021). NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization. In Proceedings - 2021 International Joint Conference on Biometrics, IJCB 2079 Article 9484336 (2021 IEEE International Joint Conference on Biometrics, IJCB 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCB52358.2021.9484336

@inproceedings{8d67f36585d046d9821e8ef5c214a0b5,

title = "NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization",

abstract = "For iris recognition in non-cooperative environments, iris segmentation has been regarded as the first most important challenge still open to the biometric community, affecting all downstream tasks from normalization to recognition. In recent years, deep learning technologies have gained significant popularity among various computer vision tasks and also been introduced in iris biometrics, especially iris segmentation. To investigate recent developments and attract more interest of researchers in the iris segmentation method, we organized the 2021 NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization (NIR-ISL 2021) at the 2021 International Joint Conference on Biometrics (IJCB 2021). The challenge was used as a public platform to assess the performance of iris segmentation and localization methods on Asian and African NIR iris images captured in non-cooperative environments. The three best-performing entries achieved solid and satisfactory iris segmentation and localization results in most cases, and their code and models have been made publicly available for reproducibility research.",

author = "Caiyong Wang and Yunlong Wang and Kunbo Zhang and Jawad Muhammad and Tianhao Lu and Qi Zhang and Qichuan Tian and Zhaofeng He and Zhenan Sun and Yiwen Zhang and Tianbao Liu and Wei Yang and Dongliang Wu and Yingfeng Liu and Ruiye Zhou and Huihai Wu and Hao Zhang and Junbao Wang and Jiayi Wang and Wantong Xiong and Xueyu Shi and Shao Zeng and Peihua Li and Haodong Sun and Jing Wang and Jiale Zhang and Qi Wang and Huijie Wu and Xinhui Zhang and Haiqing Li and Yu Chen and Liang Chen and Menghan Zhang and Ye Sun and Zhiyong Zhou and Fadi Boutros and Naser Damer and Arjan Kuijper and Juan Tapia and Andres Valenzuela and Christoph Busch and Gourav Gupta and Kiran Raja and Xi Wu and Xiaojie Li and Jingfu Yang and Hongyan Jing and Xin Wang and Bin Kong and Youbing Yin and Qi Song and Siwei Lyu and Shu Hu and Leon Premk and Matej Vitek and Vitomir Struc and Peter Peer and Khiarak, \{Jalil Nourmohammadi\} and Farhang Jaryani and Nasab, \{Samaneh Salehi\} and Moafinejad, \{Seyed Naeim\} and Yasin Amini and Morteza Noshad",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Joint Conference on Biometrics, IJCB 2021 ; Conference date: 04-08-2021 Through 07-08-2021",

year = "2021",

month = aug,

day = "4",

doi = "10.1109/IJCB52358.2021.9484336",

language = "English",

series = "2021 IEEE International Joint Conference on Biometrics, IJCB 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "Proceedings - 2021 International Joint Conference on Biometrics, IJCB 2079",

address = "United States",

}

Wang, C, Wang, Y, Zhang, K, Muhammad, J, Lu, T, Zhang, Q, Tian, Q, He, Z, Sun, Z, Zhang, Y, Liu, T, Yang, W, Wu, D, Liu, Y, Zhou, R, Wu, H, Zhang, H, Wang, J, Wang, J, Xiong, W, Shi, X, Zeng, S, Li, P, Sun, H, Wang, J, Zhang, J, Wang, Q, Wu, H, Zhang, X, Li, H, Chen, Y, Chen, L, Zhang, M, Sun, Y, Zhou, Z, Boutros, F, Damer, N, Kuijper, A, Tapia, J, Valenzuela, A, Busch, C, Gupta, G, Raja, K, Wu, X, Li, X, Yang, J, Jing, H, Wang, X, Kong, B, Yin, Y, Song, Q, Lyu, S, Hu, S, Premk, L, Vitek, M, Struc, V, Peer, P, Khiarak, JN, Jaryani, F, Nasab, SS, Moafinejad, SN, Amini, Y & Noshad, M 2021, NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization. in Proceedings - 2021 International Joint Conference on Biometrics, IJCB 2079., 9484336, 2021 IEEE International Joint Conference on Biometrics, IJCB 2021, Institute of Electrical and Electronics Engineers Inc., 2021 IEEE International Joint Conference on Biometrics, IJCB 2021, Shenzhen, China, 08/4/21. https://doi.org/10.1109/IJCB52358.2021.9484336

NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization. / Wang, Caiyong; Wang, Yunlong; Zhang, Kunbo et al.
Proceedings - 2021 International Joint Conference on Biometrics, IJCB 2079. Institute of Electrical and Electronics Engineers Inc., 2021. 9484336 (2021 IEEE International Joint Conference on Biometrics, IJCB 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - NIR Iris Challenge Evaluation in Non-cooperative Environments

T2 - 2021 IEEE International Joint Conference on Biometrics, IJCB 2021

AU - Wang, Caiyong

AU - Wang, Yunlong

AU - Zhang, Kunbo

AU - Muhammad, Jawad

AU - Lu, Tianhao

AU - Zhang, Qi

AU - Tian, Qichuan

AU - He, Zhaofeng

AU - Sun, Zhenan

AU - Zhang, Yiwen

AU - Liu, Tianbao

AU - Yang, Wei

AU - Wu, Dongliang

AU - Liu, Yingfeng

AU - Zhou, Ruiye

AU - Wu, Huihai

AU - Zhang, Hao

AU - Wang, Junbao

AU - Wang, Jiayi

AU - Xiong, Wantong

AU - Shi, Xueyu

AU - Zeng, Shao

AU - Li, Peihua

AU - Sun, Haodong

AU - Wang, Jing

AU - Zhang, Jiale

AU - Wang, Qi

AU - Wu, Huijie

AU - Zhang, Xinhui

AU - Li, Haiqing

AU - Chen, Yu

AU - Chen, Liang

AU - Zhang, Menghan

AU - Sun, Ye

AU - Zhou, Zhiyong

AU - Boutros, Fadi

AU - Damer, Naser

AU - Kuijper, Arjan

AU - Tapia, Juan

AU - Valenzuela, Andres

AU - Busch, Christoph

AU - Gupta, Gourav

AU - Raja, Kiran

AU - Wu, Xi

AU - Li, Xiaojie

AU - Yang, Jingfu

AU - Jing, Hongyan

AU - Wang, Xin

AU - Kong, Bin

AU - Yin, Youbing

AU - Song, Qi

AU - Lyu, Siwei

AU - Hu, Shu

AU - Premk, Leon

AU - Vitek, Matej

AU - Struc, Vitomir

AU - Peer, Peter

AU - Khiarak, Jalil Nourmohammadi

AU - Jaryani, Farhang

AU - Nasab, Samaneh Salehi

AU - Moafinejad, Seyed Naeim

AU - Amini, Yasin

AU - Noshad, Morteza

PY - 2021/8/4

Y1 - 2021/8/4

N2 - For iris recognition in non-cooperative environments, iris segmentation has been regarded as the first most important challenge still open to the biometric community, affecting all downstream tasks from normalization to recognition. In recent years, deep learning technologies have gained significant popularity among various computer vision tasks and also been introduced in iris biometrics, especially iris segmentation. To investigate recent developments and attract more interest of researchers in the iris segmentation method, we organized the 2021 NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization (NIR-ISL 2021) at the 2021 International Joint Conference on Biometrics (IJCB 2021). The challenge was used as a public platform to assess the performance of iris segmentation and localization methods on Asian and African NIR iris images captured in non-cooperative environments. The three best-performing entries achieved solid and satisfactory iris segmentation and localization results in most cases, and their code and models have been made publicly available for reproducibility research.

AB - For iris recognition in non-cooperative environments, iris segmentation has been regarded as the first most important challenge still open to the biometric community, affecting all downstream tasks from normalization to recognition. In recent years, deep learning technologies have gained significant popularity among various computer vision tasks and also been introduced in iris biometrics, especially iris segmentation. To investigate recent developments and attract more interest of researchers in the iris segmentation method, we organized the 2021 NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization (NIR-ISL 2021) at the 2021 International Joint Conference on Biometrics (IJCB 2021). The challenge was used as a public platform to assess the performance of iris segmentation and localization methods on Asian and African NIR iris images captured in non-cooperative environments. The three best-performing entries achieved solid and satisfactory iris segmentation and localization results in most cases, and their code and models have been made publicly available for reproducibility research.

UR - https://www.scopus.com/pages/publications/85113338158

U2 - 10.1109/IJCB52358.2021.9484336

DO - 10.1109/IJCB52358.2021.9484336

M3 - Conference contribution

AN - SCOPUS:85113338158

T3 - 2021 IEEE International Joint Conference on Biometrics, IJCB 2021

BT - Proceedings - 2021 International Joint Conference on Biometrics, IJCB 2079

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 4 August 2021 through 7 August 2021

ER -

Wang C, Wang Y, Zhang K, Muhammad J, Lu T, Zhang Q et al. NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization. In Proceedings - 2021 International Joint Conference on Biometrics, IJCB 2079. Institute of Electrical and Electronics Engineers Inc. 2021. 9484336. (2021 IEEE International Joint Conference on Biometrics, IJCB 2021). doi: 10.1109/IJCB52358.2021.9484336

NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization

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