Abstract
The introduction of technological safeguards is more important than ever, but with the increase in networks, devices, connections and applications, this it is extremely complicated. For many people, biometric security is the answer - the technology that can serve and support all industries. The biometric systems are large-scale technology implementations that have to provide capabilities in time. The aim of the current investigation is to construct a Generalized net (GN) model of biometric authentication system based on palm geometry and palm vein matching. It presents the idea of reading biometric data through a censor and camera. In the former version, via a censor placed in the housing of the device, the palm of the user is scanned. In the latter, the data is collected via a scan of the user’s veins with the camera of the device. Both variants are run simultaneously. The aims are to ease the use of smart devices, to increase the security and guarantee the protection of personal data.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Atanassov, K.: Generalized Nets. World Scientific, Singapore, New Jersey, London (1991)
Atanassov, K., Boumbarov, O., Gluhchev, G., Hadjitodorov, S., Shannon, A., Vassilev, V.: A generalized net model of biometric access-control system. In: Proceedings of the 9th WSEAS International Conference on Automatic Control, Modeling & Simulation, Istanbul, Turkey, 27–29 May 2007, pp 78–81 (2007)
Atanassov, K., et al.: Generalized nets decision making and pattern recognition. Warsaw School of Information Technology, Warszawa (2006)
Atanassov, K., Gluhchev, G., Hadjitodorov, S., Shannon, A., Vasilev, V.: Generalized nets in image processing and pattern recognition. In: Sixth International Workshop on GNs, Sofia, pp. 47–60 (2005)
Atanassov, K., Gluhchev, G., Hadjitodorov, S., Shannon, A., Vassilev, V.: Generalized Nets and Pattern Recognition. KvB Visual Concepts Pty Ltd., Monograph No. 6, Sydney (2003)
Atanassov, K., Sotirova, E.: Generalized Nets. Prof. M. Drinov Academic Publishing House, Sofia (2017). (in Bulgarian)
Atanassov, K.: On Generalized Nets Theory. “Prof. Marin Drinov” Academic Publishing House, Sofia (2007)
Bai, X., et al.: Explainable deep learning for efficient and robust pattern recognition: A survey of recent developments. Pattern Recogn. 120 (2021). IF: 7.196
Bureva, V., Sotirova, E., Bozov, H.: Generalized net model of biometric identification process. In: 2018 20th International Symposium on Electrical Apparatus and Technologies (SIELA), Bourgas, pp. 1–4 (2018)
Bureva, V., Yovcheva, P., Sotirov, S.: Generalized net model of fingerprint recognition with intuitionistic fuzzy evaluations. In: Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K., Krawczak, M. (eds.) Advances in Fuzzy Logic and Technology 2017. IWIFSGN 2017, EUSFLAT 2017. Advances in Intelligent Systems and Computing, vol. 641, pp. 286–294. Springer, Cham (2018)
Gluhchev, G., Atanassov, K., Hadjitodorov, S., Szmidt, E.: A generalized net model for signature verification. In: Conference proceedings of Tenth International Workshop on Generalized Nets, Sofia, 5 December 2009, pp. 27–30 (2009)
Gocheva, E., Sotirov, S.: Modelling of the verification by iris scanning by generalized nets. In: Conference proceedings of Ninth International Workshop on Generalized Nets, Sofia, pp 9–13 (2008)
Huo, G., Zhang, Q., Zhang, Y., et al.: Multi-source heterogeneous iris recognition using stacked convolutional deep belief networks-deep belief network model. Pattern Recogn. Image Anal. 31, 81–90 (2021)
Ikonomov, N.: GNDraw – software application for creating generalized nets. Issues Intuition. Fuzzy Sets Gener. Nets 13, 61–71 (2017)
Li, G., Wu, Z., Liu, Y., et al.: 3D hand reconstruction from a single image based on biomechanical constraints. Vis. Comput. 37, 2699–2711 (2021)
Misra S., Sridevi G., Laskar R., Modeling a virtual bare-hand interface system using a robust hand detection approach for HCI. In: Int. J. Pattern Recogn. Artif. Intell. 35(05) (2021)
Parvathi, R., Gluhchev, G., Atanassov, K.: Generalized net model of face recognition. In: Conference proceedings of Ninth International Workshop on Generalized Nets, Sofia, 4 July 2008, pp 102–105 (2008)
Ross, A., Banerjee, S., Chowdhury, A.: Security in smart cities: a brief review of digital forensic schemes for biometric data. Pattern Recogn. Lett. 138, 346–354 (2020). IF: 3.756
Sánchez-Lozano, E., Tzimiropoulos, G., Martinez, B., De la Torre, F., Valstar, M.: A functional regression approach to facial landmark tracking. IEEE Trans. Pattern Anal. Mach. Intell. 40(9), 2037–2050 (2018). IF: 16.389
Shi, L., Wang, C., Jia, H., Hu, X.: EPS: robust pupil edge points selection with Haar feature and morphological pixel patterns. Int. J. Pattern Recogn. Artif. Intell. 35(06), 2156002 (2021)
Sotirov, S.: Generalized net model of iris recognition using neural networks. Ann. Inform. Sect. Union Sci. Bulgaria 4, 127–132 (2011)
Zhang, Z.: A gait recognition method for a moving target image in sports based on a decision tree. Int. J. Biometr. 13(2/3), 165–179 (2021)
Acknowledgment
The authors are grateful for the support provided by the Bulgarian Ministry of Education and Science under the National Research Programme “Information and Communication Technologies for a Digital Single Market in Science, Education and Security” approved by DCM # 577/ 17.08.2018.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Ivanova, Z., Bureva, V. (2022). Generalized Net Model of Biometric Authentication System Based on Palm Geometry and Palm Vein Matching. In: Sotirov, S.S., Pencheva, T., Kacprzyk, J., Atanassov, K.T., Sotirova, E., Staneva, G. (eds) Contemporary Methods in Bioinformatics and Biomedicine and Their Applications. BioInfoMed 2020. Lecture Notes in Networks and Systems, vol 374. Springer, Cham. https://doi.org/10.1007/978-3-030-96638-6_13
Download citation
DOI: https://doi.org/10.1007/978-3-030-96638-6_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-96637-9
Online ISBN: 978-3-030-96638-6
eBook Packages: EngineeringEngineering (R0)