Face Recognition Based Attendance System

Authors

  • Mr. Charan Pote Assistant Professor, Department of Computer Technology, PCE, Nagpur, India
  • Prachi Somkuwar UG Students, Department of Computer Technology, PCE, Nagpur, India
  • Kajal Raut UG Students, Department of Computer Technology, PCE, Nagpur, India
  • Yogini Chambare UG Students, Department of Computer Technology, PCE, Nagpur, India
  • Nihal Borkar UG Students, Department of Computer Technology, PCE, Nagpur, India

Keywords:

Face Detection, Face Recognition, Haar Cascade Classifier

Abstract

In the traditional system, it is hard to be handle the attendance of huge students in a classroom. As it is time- consuming and has a high probability of error during the process of inputting data into the computer. Real-Time Face Recognition is a real-world solution which comes with dayto day activities of handling a bulk of student’s attendance. Face Recognition is a process of recognizing the students face for taking attendance by using face biometrics. In this project, a computer system will be able to find and recognize human faces fast that are being captured through a surveillance camera. Numerous algorithms and techniques have been developed for improving the performance of face recognition but our proposed system uses Haar cascade classifier to find the positive and negative of the face and LBPH (Local binary pattern histogram) algorithm for face recognition by using python programming and OpenCV library. Here we use the tkinter GUI interface for user interface purpose.

References

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https://www.slideshare.net/ShreyaDand avate/face-recognition-attendance- system96913577

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Published

18-04-2022

How to Cite

Mr. Charan Pote, Prachi Somkuwar, Kajal Raut, Yogini Chambare, & Nihal Borkar. (2022). Face Recognition Based Attendance System. International Journal for Research Publication and Seminar, 13(3), 23–27. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/519

Issue

Vol. 13 No. 3 (2022): Volume 13 | Issue 3 | 2022 (NSCIT)

Section

Original Research Article

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