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Attendance System Using Face Recognition

EasyChair Preprint no. 9325

4 pagesDate: November 16, 2022


The face is the crucial part of the human body that uniquely identifies a person. Using face characteristics as biometrics, the face recognition system can be implemented. The most demanding task in any organization is attendance marking. In the traditional attendance system, the students are called out by the teachers, and their presence or absence is marked accordingly. However, these traditional techniques are time-consuming and tedious. In this project, the Open CV-based face recognition approach has been proposed. This model integrates a camera that captures an input image, an algorithm for detecting a face from an input image, encoding and identifying the face, marking the attendance in a spreadsheet, and converting it into a PDF file. The training database is created by training the system with the faces of the authorized students. The cropped images are then stored as a database with respective labels. The features are extracted using the LBPH algorithm.

Keyphrases: Attendance, Biometrics, face recognition, Open CV

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Sagar Bank and Akhilesh Burungale and Balkrishna Giri},
  title = {Attendance System Using Face Recognition},
  howpublished = {EasyChair Preprint no. 9325},

  year = {EasyChair, 2022}}
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