Cloud Based Face Recognition using Machine Learning

Authors

  • Pramod R  Computer Science and Engineering, Nagarjuna College of Engineering and Techology, Bengaluru, Karnataka, India
  • Rakshanda D. Bellary  Computer Science and Engineering, Nagarjuna College of Engineering and Techology, Bengaluru, Karnataka, India
  • Riya Bharti  Computer Science and Engineering, Nagarjuna College of Engineering and Techology, Bengaluru, Karnataka, India
  • Sushma S  Computer Science and Engineering, Nagarjuna College of Engineering and Techology, Bengaluru, Karnataka, India

DOI:

https://doi.org/10.32628/IJSRST2183217

Keywords:

Face Recognition, Keypad, Cloud, Authentication, Pi Camera.

Abstract

The main motive of this paper is to implement a system where the employees and the visitors are granted access to enter the office by recognizing their face images. And henceforth, the access is granted only when the employee or the visitor enters the correct pin into the keypad which is concerned for authentication purpose.Without any usage of the tag keys or identity card an employee can easily unlock the entrance door once his face is recognized. A Raspberry pi, a camera, a memory card and a keypad is the hardware components that is required in this system. The face recognition and the authentication carried out by the keypad is controlled by the cloud based platforms and the local based Web Services. The authentication mechanism and the face recognition provides a safe and and increased level of security which gives a protection against spoofing attacks where there is no need of carrying any tag keys or access cards.

References

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Published

2021-06-30

Issue

Section

Research Articles

How to Cite

[1]
Pramod R, Rakshanda D. Bellary, Riya Bharti, Sushma S "Cloud Based Face Recognition using Machine Learning" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 8, Issue 3, pp.1003-1006, May-June-2021. Available at doi : https://doi.org/10.32628/IJSRST2183217