Skip to main content
SpringerLink
Log in

Towards Mobile Palmprint Biometric System with the New Palmprint Database

  • Conference paper
  • First Online:
Image Processing and Communications (IP&C 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1062))

Included in the following conference series:

  • 669 Accesses

Abstract

In this paper, we address the challenge of palmprint-based human verification in the mobile scenario. We propose a novel way of palmprint acquisition that will be used in order to create a new palmprint benchmark dataset. The palmprints are acquired by the handheld devices using an application dedicated to the Android operating system. The application provides the graphical assistant that improves the hand positioning and ROI extraction. It enables acquiring samples of both hands, in unconstrained illumination conditions, with different backgrounds. After the acquisition, each sample is evaluated according to color and rejected if it does not meet the requirements. So far, there are not many mobile biometrics databases acquired in an unconstrained environment and meeting privacy and legal requirements.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. CASIA. http://biometrics.idealtest.org/index.jsp. Accessed 12 Feb 2019

  2. Chai, T., Wang, S., Sun, D.: A palmprint ROI extraction method for mobile devices in complex environment. In: 2016 IEEE 13th International Conference on Signal Processing (ICSP), pp. 1342–1346. IEEE (2016)

    Google Scholar 

  3. Choraś, M., Kozik, R.: Contactless palmprint and knuckle biometrics for mobile devices. Pattern Anal. Appl. 15(1), 73–85 (2012)

    Article  MathSciNet  Google Scholar 

  4. Clarke, R.: Human identification in information systems: management challenges and public policy issues. Inf. Technol. People 7(4), 6–37 (1994)

    Article  Google Scholar 

  5. Das, A., Galdi, C., Han, H., Ramachandra, R., Dugelay, J.L., Dantcheva, A.: Recent advances in biometric technology for mobile devices. In: 9th IEEE International Conference on Biometrics: Theory, Applications and Systems, BTAS 2018 (2018)

    Google Scholar 

  6. Gao, F., Leng, L., Zeng, J.: Palmprint recognition system with double-assistant-point on iOS mobile devices. In: Proceedings of the 29th British Machine Vision Conference, BMVC 2018 (2018)

    Google Scholar 

  7. IITD. http://www4.comp.polyu.edu.hk/~csajaykr/database.php. Accessed 12 Feb 2019

  8. Ito, K., Aoki, T.: Recent advances in biometric recognition. ITE Trans. Media Technol. Appl. 6(1), 64–80 (2018)

    Article  Google Scholar 

  9. Jia, W., Zhang, B., Lu, J., Zhu, Y., Zhao, Y., Zuo, W., Ling, H.: Palmprint recognition based on complete direction representation. IEEE Trans. Image Process. 26(9), 4483–4498 (2017)

    Article  MathSciNet  Google Scholar 

  10. Kim, J.S., Li, G., Son, B., Kim, J.: An empirical study of palmprint recognition for mobile phones. IEEE Trans. Consum. Electron. 61(3), 311–319 (2015)

    Article  Google Scholar 

  11. Kindt, E.: Having yes, using no? About the new legal regime for biometric data. Comput. Law Secur. Rev. 34(3), 523–538 (2018)

    Article  Google Scholar 

  12. Leng, L., Gao, F., Chen, Q., Kim, C.: Palmprint recognition system on mobile devices with double-line-single-point assistance. Pers. Ubiquit. Comput. 22(1), 93–104 (2018)

    Article  Google Scholar 

  13. Moco, N.F., Técnico, I.S., de Telecomunicações, I., Correia, P.L.: Smartphone-based palmprint recognition system. In: 2014 21st International Conference on Telecommunications (ICT), pp. 457–461. IEEE (2014)

    Google Scholar 

  14. PolyU. http://www4.comp.polyu.edu.hk/~biometrics. Accessed 12 Feb 2019

  15. Qu, X., Zhang, D., Lu, G.: A novel line-scan palmprint acquisition system. IEEE Trans. Syst. Man Cybern. Syst. 46(11), 1481–1491 (2016)

    Article  Google Scholar 

  16. Sanchez-Reillo, R., Ortega-Fernandez, I., Ponce-Hernandez, W., Quiros-Sandoval, H.C.: How to implement EU data protection regulation for R&D in biometrics. Comput. Stand. Interfaces 61, 89–96 (2019)

    Article  Google Scholar 

  17. UE: Regulation 2016/679 of the European parliament and of the council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data. http://eur-lex.europa.eu/eli/reg/2016/679/oj. Accessed 12 Feb 2019

  18. Ungureanu, A.S., Thavalengal, S., Cognard, T.E., Costache, C., Corcoran, P.: Unconstrained palmprint as a smartphone biometric. IEEE Trans. Consum. Electron. 63(3), 334–342 (2017)

    Article  Google Scholar 

  19. Verma, S., Chandran, S.: Contactless palmprint verification system using 2-D Gabor filter and principal component analysis. Int. Arab J. Inf. Technol. 16(1), 23–29 (2019)

    Google Scholar 

  20. Wojciechowska, A., Choraś, M., Kozik, R.: Evaluation of the pre-processing methods in image-based palmprint biometrics. In: International Conference on Image Processing and Communications, pp. 43–48. Springer (2017)

    Google Scholar 

  21. Zhang, D.D., Kong, W., You, J., Wong, M.: Online palmprint identification. IEEE Trans. Pattern Anal. Mach. Intell. 25, 1041–1050 (2003)

    Article  Google Scholar 

  22. Zhang, D.D., et al.: Palmprint Authentication, vol. 3. Springer, New York (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology, Bydgoszcz, Poland

    Agata Giełczyk, Karolina Dembińska, Michał Choraś & Rafał Kozik

Authors
  1. Agata Giełczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Karolina Dembińska
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michał Choraś
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rafał Kozik
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Agata Giełczyk .

Editor information

Editors and Affiliations

  1. Institute of Telecommunications and Computer Science, University of Science and Technology (UTP), Bydgoszcz, Poland

    Michał Choraś

  2. Department of Telecommunications, Computer Sciences and Electrical Engineering, University of Science and Technology (UTP), Bydgoszcz, Poland

    Ryszard S. Choraś

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Giełczyk, A., Dembińska, K., Choraś, M., Kozik, R. (2020). Towards Mobile Palmprint Biometric System with the New Palmprint Database. In: Choraś, M., Choraś, R. (eds) Image Processing and Communications. IP&C 2019. Advances in Intelligent Systems and Computing, vol 1062. Springer, Cham. https://doi.org/10.1007/978-3-030-31254-1_19

Download citation

Publish with us

Policies and ethics

Search

Navigation