Modeling and implementation of an automatic Access control system for secure permises using facial recognition

Modeling and implementation of an automatic Access control system for secure permises using facial recognition

Authors

  • Bopatriciat Boluma Mangata University of Kinshasa
  • Kisiaka Mbambi Faculty of Computer science, University of Reverend Kim
  • Kadima Muamba Faculty of Computer science, University of Reverend Kim
  • Fundji khalaba Departement of Mathematics and Computer science, University of Kinshasa

DOI:

https://doi.org/10.24191/jcrinn.v7i2.273

Keywords:

Embedded system, Biometrics, Access control, Automation, Facial recognition, Pattern recognition

Abstract

Security is a major concern within companies to prevent access to information by unauthorized persons.  In this work, we are interested in access control through facial recognition. To realize this access control system based on facial recognition, we used an embedded system under Arduino which gives us the possibility to assemble the performances of programming and electronics, more precisely, we programmed electronic systems for the automatic opening of doors without the action of a human being. From a sample of 100 individuals composed of 40 women and 60 men, 75 of whom were registered and 25 non-registered, our access control system obtained the results of 70 true positives, 5 false negatives, 8 false positives and 17 true negatives that constitute our confusion matrix. However, from the set of tests performed we can conclude that multi-modality fusion can be leveraged to increase the performance of the verification system as the verification performance of multimodal systems (feature fusion or score fusion) can be applied to give even better results.

Downloads

Download data is not yet available.

References

Benaliouche, H., & Touahria, M. (2014). Comparative study of multimodal biometric recognition by fusion of iris and fingerprint. The Scientific World Journal, 2014.

Bopatriciat Boluma Mangata et al. (2022). Performance evaluation of a single access contol system. journal of research in engeneering and applied sciences. Volume (7 Issue 01), p4-6.

Bopatriciat Boluma Mangata et al. (2021). Contribution of an Embedded and Biometric System in a Replicated Database for Access Control in a Multi-Entry Institution. International Journal of Science and Research (IJSR), Volume (10 Issue 3), p2-5.

Bowers, D. M. (2013). Access control and personal identification systems. Butterworth-Heinemann.

Douaa, M. E. C. H. T. A., & Radhwane, G. H. E. R. B. I. (2019). Automatisation Des Taches Domotiques D’une Maison A L’aide D’une Carte Arduino Et Labview (Doctoral Dissertation, Universite Mohamed Boudiaf-M’sila).

Guizani, M., Zavala, M. L., & Funamizu, N. (2016). Assessment of endotoxin removal from reclaimed wastewater using coagulation-flocculation. Journal of Water Resource and Protection, 8(9), 855-864.

Markoulidakis, I., Rallis, I., Georgoulas, I., Kopsiaftis, G., Doulamis, A., & Doulamis, N. (2021). Multiclass Confusion Matrix Reduction Method and Its Application on Net Promoter Score Classification Problem. Technologies, 9(4), 81.

Mathivet, V. (2017). L'intelligence artificielle pour les développeurs: concepts et implémentations en C#. Éditions ENI..

Norman, T. L. (2011). Electronic access control. Elsevier.

Wirotius, M. (2005). Authentification par signature manuscrite sur support nomade (Doctoral dissertation, Tours).

Downloads

Published

2022-09-30

How to Cite

Boluma Mangata, B., Reagan, Donatien, & Joseph. (2022). Modeling and implementation of an automatic Access control system for secure permises using facial recognition. Journal of Computing Research and Innovation, 7(2), 11–22. https://doi.org/10.24191/jcrinn.v7i2.273

Issue

Section

General Computing
Loading...