Updating the Biometric Template by Assessing the Quality of the Original Data
Biometric features used in recognition systems are subject to aging. In addition, there may be variations in working conditions that are not taken into account when registering a user. Therefore, one of the tasks that must be solved when building a universal and long-term functioning biometric syste...
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| Published in | Journal of computer & systems sciences international Vol. 61; no. 3; pp. 413 - 420 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Moscow
Pleiades Publishing
01.06.2022
Springer Nature B.V |
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| Abstract | Biometric features used in recognition systems are subject to aging. In addition, there may be variations in working conditions that are not taken into account when registering a user. Therefore, one of the tasks that must be solved when building a universal and long-term functioning biometric system is updating the biometric template. An algorithm for updating a biometric template is proposed that uses an estimate of the distance from the presented biometric features to the user’s features registered under ideal conditions. Such an estimate is calculated by a neural network trained on a database with a large variability in registration conditions. The algorithm is tested on a face recognition system. |
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| AbstractList | Biometric features used in recognition systems are subject to aging. In addition, there may be variations in working conditions that are not taken into account when registering a user. Therefore, one of the tasks that must be solved when building a universal and long-term functioning biometric system is updating the biometric template. An algorithm for updating a biometric template is proposed that uses an estimate of the distance from the presented biometric features to the user’s features registered under ideal conditions. Such an estimate is calculated by a neural network trained on a database with a large variability in registration conditions. The algorithm is tested on a face recognition system. |
| Author | Solomatin, I. A. Kubentaeva, S. B. Matveev, I. A. |
| Author_xml | – sequence: 1 givenname: I. A. surname: Solomatin fullname: Solomatin, I. A. email: ivan.solomatin@phystech.edu organization: Moscow Institute of Physics and Technology, Samsung R&D Institute Russia – sequence: 2 givenname: I. A. surname: Matveev fullname: Matveev, I. A. email: matveev@ccas.ru organization: Federal Research Center “Computer Science and Control,” Russian Academy of Sciences – sequence: 3 givenname: S. B. surname: Kubentaeva fullname: Kubentaeva, S. B. organization: Moscow Institute of Physics and Technology, Samsung R&D Institute Russia |
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| Copyright | Pleiades Publishing, Ltd. 2022. ISSN 1064-2307, Journal of Computer and Systems Sciences International, 2022, Vol. 61, No. 3, pp. 413–420. © Pleiades Publishing, Ltd., 2022. Russian Text © The Author(s), 2022, published in Izvestiya Akademii Nauk, Teoriya i Sistemy Upravleniya, 2022, No. 3, pp. 122–129. |
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| References | D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” arXiv: 1412.6980 (2014). JainA. K.RossA.Handbook of Biometrics2008BerlinSpringer10.1007/978-0-387-71041-9 J. Carls, R. Raines, M. Grimaila, and S. Rogers, “Biometric security enhancements through template aging matching score analysis,” in Proceedings of the 3rd International Conference on Information Warfare and Security, Omaha, NE, USA,2008. GeorghiadesA. S.BelhumeurP. N.KriegmanD. J.From few to many: Illumination cone models for face recognition under variable lighting and poseIEEE Trans. Pattern Anal. Mach. Intell.20012364366010.1109/34.927464 InsightFace: 2D and 3D Face Analysis Project. https://github.com/deepinsight/insightface. Accessed November 8, 2021. G. Hasse and A. Wolf, “Data quality, interoperability, biometrics fusion, and template ageing: Challenges for epassports,” in Proceedings of the Biometric Consortium Conference, Arlington, VA, USA (2005). UludagU.RossA.JainA.Biometric template selection and update: A case study in fingerprintsPattern Recogn.2004371533154210.1016/j.patcog.2003.11.012 A. Rattani, G. L. Marcialis, and F. Roli, “Biometric template update using the graph mincut algorithm: A case study in face verification,” in Proceedings of the IEEE Biometrics Symposium, Tampa, FL, USA (2008), pp. 23–28. GneushevA. N.KovkovD. V.MatveevI. A.NovikV. P.Optimizing the selection of a biometric template from a sequenceJ. Comput. Syst. Sci. Int.201554399337652210.1134/S1064230715030077 G. Lovisotto, S. Eberz, and I. Martinovic, “Biometric backdoors: A poisoning attack against unsupervised template updating,” in Proceedings of the IEEE European Symposium on Security and Privacy, Genova, Italy (2020), pp. 184–197. LantinisA.A survey of the effects of aging on biometric identity verificationInt. J. Biometr.20102345210.1504/IJBM.2010.030415 B. Freni, G. L. Marcialis, and F. Roli, “Replacement algorithms for fingerprint template update,” in Proceedings of the International Conference on Image Analysis and Recognition (Springer, Berlin, 2008), pp. 884–893. S. Kirchgasser and A. Uhl, “Template ageing in non-minutiae fingerprint recognition,” in Proceedings of the 5th International Workshop Biometrics and Forensics, Coventry, UK,2017, pp. 1–5. S. Chen, Y. Liu, X. Gao, and Zh. Han, “Mobilefacenets: Efficient CNNs for accurate real-time face verification on mobile devices,” in Proceedings of the Chinese Conference on Biometric Recognition (Springer, Cham, 2018), pp. 428–438. RamanathanN.ChellappaR.Face verification across age progressionIEEE Trans. Image Process.2006153349336110.1109/TIP.2006.881993 Y. LeCun, B. Boser, J. S. Denker, et al., “Handwritten digit recognition with a back-propagation network,” Adv. Neural Inform. Process. Syst. 2 (1989). A. Czajka, “Template ageing in iris recognition,” in Proceedings of the International Conference on Bio-inspired Systems and Signal Processing, Barcelona, Spain (2013), pp. 70–78. HollingsworthK.BowyerK.FlynnP.Advances in Biometrics2009 MarcialisG. L.RattaniA.RoliF.Structural, Syntactic, and Statistical Pattern Recognition2008 7293_CR7 7293_CR6 7293_CR11 7293_CR5 7293_CR10 7293_CR4 7293_CR17 7293_CR16 U. Uludag (7293_CR13) 2004; 37 7293_CR14 N. Ramanathan (7293_CR3) 2006; 15 A. K. Jain (7293_CR1) 2008 A. Lantinis (7293_CR2) 2010; 2 A. S. Georghiades (7293_CR15) 2001; 23 7293_CR19 7293_CR18 A. N. Gneushev (7293_CR8) 2015; 54 K. Hollingsworth (7293_CR9) 2009 G. L. Marcialis (7293_CR12) 2008 |
| References_xml | – reference: InsightFace: 2D and 3D Face Analysis Project. https://github.com/deepinsight/insightface. Accessed November 8, 2021. – reference: GeorghiadesA. S.BelhumeurP. N.KriegmanD. J.From few to many: Illumination cone models for face recognition under variable lighting and poseIEEE Trans. Pattern Anal. Mach. Intell.20012364366010.1109/34.927464 – reference: GneushevA. N.KovkovD. V.MatveevI. A.NovikV. P.Optimizing the selection of a biometric template from a sequenceJ. Comput. Syst. Sci. Int.201554399337652210.1134/S1064230715030077 – reference: G. Hasse and A. Wolf, “Data quality, interoperability, biometrics fusion, and template ageing: Challenges for epassports,” in Proceedings of the Biometric Consortium Conference, Arlington, VA, USA (2005). – reference: J. Carls, R. Raines, M. Grimaila, and S. Rogers, “Biometric security enhancements through template aging matching score analysis,” in Proceedings of the 3rd International Conference on Information Warfare and Security, Omaha, NE, USA,2008. – reference: S. Chen, Y. Liu, X. Gao, and Zh. Han, “Mobilefacenets: Efficient CNNs for accurate real-time face verification on mobile devices,” in Proceedings of the Chinese Conference on Biometric Recognition (Springer, Cham, 2018), pp. 428–438. – reference: D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” arXiv: 1412.6980 (2014). – reference: LantinisA.A survey of the effects of aging on biometric identity verificationInt. J. Biometr.20102345210.1504/IJBM.2010.030415 – reference: HollingsworthK.BowyerK.FlynnP.Advances in Biometrics2009 – reference: JainA. K.RossA.Handbook of Biometrics2008BerlinSpringer10.1007/978-0-387-71041-9 – reference: UludagU.RossA.JainA.Biometric template selection and update: A case study in fingerprintsPattern Recogn.2004371533154210.1016/j.patcog.2003.11.012 – reference: MarcialisG. L.RattaniA.RoliF.Structural, Syntactic, and Statistical Pattern Recognition2008 – reference: Y. LeCun, B. Boser, J. S. Denker, et al., “Handwritten digit recognition with a back-propagation network,” Adv. Neural Inform. Process. Syst. 2 (1989). – reference: A. Czajka, “Template ageing in iris recognition,” in Proceedings of the International Conference on Bio-inspired Systems and Signal Processing, Barcelona, Spain (2013), pp. 70–78. – reference: S. Kirchgasser and A. Uhl, “Template ageing in non-minutiae fingerprint recognition,” in Proceedings of the 5th International Workshop Biometrics and Forensics, Coventry, UK,2017, pp. 1–5. – reference: G. Lovisotto, S. Eberz, and I. Martinovic, “Biometric backdoors: A poisoning attack against unsupervised template updating,” in Proceedings of the IEEE European Symposium on Security and Privacy, Genova, Italy (2020), pp. 184–197. – reference: A. Rattani, G. L. Marcialis, and F. Roli, “Biometric template update using the graph mincut algorithm: A case study in face verification,” in Proceedings of the IEEE Biometrics Symposium, Tampa, FL, USA (2008), pp. 23–28. – reference: B. Freni, G. L. Marcialis, and F. Roli, “Replacement algorithms for fingerprint template update,” in Proceedings of the International Conference on Image Analysis and Recognition (Springer, Berlin, 2008), pp. 884–893. – reference: RamanathanN.ChellappaR.Face verification across age progressionIEEE Trans. Image Process.2006153349336110.1109/TIP.2006.881993 – volume: 54 start-page: 399 year: 2015 ident: 7293_CR8 publication-title: J. Comput. Syst. Sci. Int. doi: 10.1134/S1064230715030077 – volume: 37 start-page: 1533 year: 2004 ident: 7293_CR13 publication-title: Pattern Recogn. doi: 10.1016/j.patcog.2003.11.012 – volume: 15 start-page: 3349 year: 2006 ident: 7293_CR3 publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2006.881993 – ident: 7293_CR17 doi: 10.1007/978-3-319-97909-0_46 – ident: 7293_CR11 doi: 10.1109/EuroSP48549.2020.00020 – ident: 7293_CR4 – volume: 23 start-page: 643 year: 2001 ident: 7293_CR15 publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.927464 – ident: 7293_CR6 – volume-title: Structural, Syntactic, and Statistical Pattern Recognition year: 2008 ident: 7293_CR12 – ident: 7293_CR14 doi: 10.1109/BSYM.2008.4655518 – ident: 7293_CR7 doi: 10.1109/AFGR.2008.4813331 – ident: 7293_CR10 doi: 10.1007/978-3-540-69812-8_88 – ident: 7293_CR18 – ident: 7293_CR5 doi: 10.1109/IWBF.2017.7935091 – ident: 7293_CR19 – ident: 7293_CR16 – volume-title: Advances in Biometrics year: 2009 ident: 7293_CR9 – volume-title: Handbook of Biometrics year: 2008 ident: 7293_CR1 doi: 10.1007/978-0-387-71041-9 – volume: 2 start-page: 34 year: 2010 ident: 7293_CR2 publication-title: Int. J. Biometr. doi: 10.1504/IJBM.2010.030415 |
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| SubjectTerms | Algorithms Artificial Intelligence Control Engineering Face recognition Feature recognition Mechatronics Neural networks Quality assessment Robotics |
| Title | Updating the Biometric Template by Assessing the Quality of the Original Data |
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