Face Recognition Based Automated Attendance Management System

Author:

Aparna Trivedi 1,Chandan Mani Tripathi 2,Dr. Yusuf Perwej 3,Ashish Kumar Srivastava 4,Neha Kulshrestha 4

Affiliation:

1. B.Tech Scholar, Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, India

2. Assistant Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow , India

3. Professor, Department of Computer Science & Engineering, Ambalika Institute of Management and Technology, Lucknow, India

4. Assistant Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, India

Abstract

At the beginning and end of each session, attendance is an important aspect of the daily classroom evaluation. When using traditional methods such as calling out roll calls or taking a student's signature, managing attendance can be a time-consuming task. The teacher normally checks it, although it's possible that a teacher will miss someone or some students' answers many times. Face recognition-based attendance system is a solution to the problem of recognizing faces for the purpose of collecting attendance by utilizing face recognition technology based on high-definition monitor video and other information technology. Instead of depending on time-consuming approaches, we present a real-time Face Recognition System for tracking student attendance in class in this work. The suggested method included identifying human faces from a webcam using the Viola-Jones technique, resizing the identified face to the desired size, and then processing the resized face using a basic Local Binary Patterns Histogram algorithm. After the recognition is completed, the attendance will be immediately updated in a SQLite database with the relevant information. Many institutions will profit greatly from this endeavor. As a result, the amount of time it takes and the number of human errors it makes are minimized, making it more efficient.

Publisher

Technoscience Academy

Subject

General Medicine

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Attendance Management System Using Image andVoice Recognition;International Journal of Innovative Science and Research Technology (IJISRT);2024-08-08

2. Sensing Human Emotion using Emerging Machine Learning Techniques;International Journal of Scientific Research in Science, Engineering and Technology;2024-07-22

3. IMPROVING E-LEARNING BY FACIAL EXPRESSION ANALYSIS;Applied Computer Science;2024-06-30

4. Attendance Management with Facial Recognition using OpenCV;2024 5th International Conference for Emerging Technology (INCET);2024-05-24

5. Biometric Facial Driven Digital Attendance System using Machine Learning Approach Based on Haar Cascade Technique;2024 1st International Conference on Cognitive, Green and Ubiquitous Computing (IC-CGU);2024-03-01

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