Skip to main content

RecogApp - Web and Mobile Application to Recognition Support

  • Conference paper
  • First Online:
Human Systems Engineering and Design II (IHSED 2019)

Abstract

Over time, with the advancement of technology and the number of devices increasing to be launched in the market, namely smartphones, tablets, hybrids and laptops, it is essential to have advances in digital security and in forms of authentication. These forms of authentication have become increasingly. This article presents a system consisting of a web platform and a mobile application for android, with the objective of supporting researchers in the development, improvement and testing of facial recognition and iris recognition algorithms. This system will store large quantities of images sent voluntarily, obeying the particularities of studies defined by researchers to which users adhere, these images are taken in environments with different characteristics, considering several accessories and in several places, in order to increase the number of cases of possible analyzes for development and/or use of recognition algorithms.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
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. Abdel-Kader, R.F., Atta, R., El-Shakhabe, S.: An efficient eye detection and tracking system based on particle swarm optimization and adaptive block-matching search algorithm. Eng. Appl. Artif. Intell. 31, 90–100 (2014)

    Article  Google Scholar 

  2. Adwan, S., Arof, H.: Modified integral projection method for eye detection using dynamic time warping. Int. J. Innov. Comput. Inf. Control 8(1A), 187–200 (2012)

    Google Scholar 

  3. Bhoi, N., Mohanty, M.N.: Template matching based eye detection in facial image. Int. J. Comput. Appl. 12(5), 15–18 (2010)

    Google Scholar 

  4. Hassaballah, M., Murakami, K.: An automatic eye detection method for gray intensity facial images. Int. J. Comput. Sci. Issues (IJCSI) 8(2), 272–282 (2011)

    Google Scholar 

  5. Jung, C., Sun, T., Jiao, L.: Eye detection under varying illumination using the retinex theory. Neurocomputing 113, 130–137 (2013)

    Article  Google Scholar 

  6. Liu, H., Liu, Q.: Robust real-time eye detection and tracking for rotated facial images under complex conditions. In: Proceedings of the 2010 6th International Conference on Natural Computation, ICNC 2010, vol. 4, no. ICNC, pp. 2028–2034 (2010)

    Google Scholar 

  7. Nanni, L., Lumini, A.: Combining face and eye detectors in a high-performance face-detection system. IEEE Multimedia 19(4), 20–27 (2012)

    Article  Google Scholar 

  8. Orman, Z., Battal, A., Kemer, E.: A study on face, eye detection and gaze estimation. Int. J. Comput. Sci. Eng. Surv. 2(3), 29–46 (2011)

    Article  Google Scholar 

  9. Park, C.W., Park, K.T., Moon, Y.S.: Eye detection using eye filter and minimisation of NMF-based reconstruction error in facial image. Electron. Lett. 46(2), 130 (2010)

    Article  Google Scholar 

  10. Soetedjo, A.: Eye detection based-on color and shape features. Int. J. Adv. Comput. Sci. Appl. 3(5), 17–22 (2013)

    Google Scholar 

  11. Wu, Y., Ji, Q.: Learning the deep features for eye detection in uncontrolled conditions. In: Proceedings of the International Conference on Pattern Recognition, pp. 455–459 (2014)

    Google Scholar 

  12. Thomas, T., George, A., Devi, K.P.I.: Effective iris recognition system. Procedia Technol. 25, 464–472 (2016)

    Article  Google Scholar 

  13. Daugman, J.: New methods in IRIS recognition. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 37(5), 1167–1175 (2007)

    Article  Google Scholar 

  14. Wildes, R.P.: Iris recognition: an emerging biometric technology. Proc. IEEE 85(9), 1348–1363 (1997)

    Article  Google Scholar 

  15. Verma, S.J., Saxena, D., Gautam, R., Kaushal, L.: IRIS recognition system. Int. J. Eng. Adv. Technol. 2(6), 239–244 (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to André Esteves , João Jesus , Ângela Oliveira or Filipe Fidalgo .

Editor information

Editors and Affiliations

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

Esteves, A., Jesus, J., Oliveira, Â., Fidalgo, F. (2020). RecogApp - Web and Mobile Application to Recognition Support. In: Ahram, T., Karwowski, W., Pickl, S., Taiar, R. (eds) Human Systems Engineering and Design II. IHSED 2019. Advances in Intelligent Systems and Computing, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-27928-8_99

Download citation

Publish with us

Policies and ethics