Facial Biometrics Driven Attendance Automation Solution Using LBPH Algorithm

Year : 2024 | Volume :11 | Issue : 01 | Page : 27-35
By

    Yashdeep Singh Maurya

  1. Anurag Agarwal

  2. Manogya Singh

  3. Amit Karmakar

  1. Student, Department of Computer Science and Engineering, Shri Ram Murti Smarak College of Engg. and Technology, Bareilly, Uttar Pradesh, India
  2. Student, Department of Computer Science and Engineering, Shri Ram Murti Smarak College of Engg. and Technology, Bareilly, Uttar Pradesh, India
  3. Student, Department of Computer Science and Engineering, Shri Ram Murti Smarak College of Engg. and Technology, Bareilly, Uttar Pradesh, India
  4. Student, Department of Computer Science and Engineering, Shri Ram Murti Smarak College of Engg. and Technology, Bareilly, Uttar Pradesh, India

Abstract

In today’s educational landscape, managing attendance remains a central administrative task, often conducted manually on paper, consuming valuable time for educators. This project proposes a solution utilizing facial recognition technology to streamline the attendance process, thereby saving time and maintaining accurate student records. The objective is to develop an automated attendance system that is minimally intrusive, cost-effective, and highly efficient, leveraging computer vision techniques and algorithms like local binary patterns (LBP) implemented in Python. OpenCV libraries offer comprehensive functionality for operations such as face detection, training, and testing, facilitating seamless integration into the system. The process involves two key components: face detection and face recognition. Initially, face detection identifies and captures the facial features of students, storing this data in a dataset. Subsequently, during attendance sessions, the system compares captured images with those in the dataset. Upon a match, attendance is automatically recorded, associating the student’s presence with the date and time in a CSV file. By harnessing the power of facial recognition technology and advanced algorithms, this project aims to revolutionize attendance management in educational institutions, offering a faster, more accurate, and convenient alternative to traditional methods.

Keywords: Local binary pattern (LBP), OpenCV (open-source computer vision library), CSV (comma-separated values), Python, attendance automation

[This article belongs to Journal of Open Source Developments(joosd)]

How to cite this article: Yashdeep Singh Maurya, Anurag Agarwal, Manogya Singh, Amit Karmakar , Facial Biometrics Driven Attendance Automation Solution Using LBPH Algorithm joosd 2024; 11:27-35
How to cite this URL: Yashdeep Singh Maurya, Anurag Agarwal, Manogya Singh, Amit Karmakar , Facial Biometrics Driven Attendance Automation Solution Using LBPH Algorithm joosd 2024 {cited 2024 Apr 15};11:27-35. Available from: https://journals.stmjournals.com/joosd/article=2024/view=143425


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Regular Issue Subscription Review Article
Volume 11
Issue 01
Received April 3, 2024
Accepted April 8, 2024
Published April 15, 2024
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