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Integrated Student Database and Attendance Management System with Face Recognition

EasyChair Preprint no. 10400

8 pagesDate: June 14, 2023


The Integrated Student Database and Attendance Management System with Face Recognition is an innovative solution designed to streamline and enhance attendance tracking and management processes within educational institutions. This system leverages the power of face recognition technology to accurately and efficiently monitor student attendance, eliminating the need for manual methods such as roll call or barcode scanning. The primary objective of this system is to create a comprehensive and centralized student database that seamlessly integrates with attendance management. By using face recognition technology, the system can reliably identify and authenticate students, ensuring accurate attendance records. The system captures facial images of students during registration, which are then stored securely in the database. During class sessions, the system utilizes video feeds from camera used in the system to continuously analyze and match faces with the stored images in real-time. This process enables instant identification of students present in the classroom, automating the attendance marking process. Furthermore, the system can generate attendance reports for the class and for the entire institute. The integrated database component of the system provides a centralized repository for storing student information, including personal details and attendance history. This allows administrators and teachers to access up-to-date and accurate data, promoting effective communication and informed decision-making. By implementing the Integrated Student Database and Attendance Management System with Face Recognition, educational institutions can streamline attendance management processes, save administrative time, reduce errors, and enhance overall efficiency. This system offers a reliable and scalable solution to optimize student attendance tracking, promote accountability, and improve communication among stakeholders in the educational ecosystem.

Keyphrases: face detection, face recognition, image processing, LBPH

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Siddhesh Salunkhe and Rakesh Lad and Shishupal Kumar and Tanishq Mehta and Ravindra Bhegade},
  title = {Integrated Student Database and Attendance Management System with Face Recognition},
  howpublished = {EasyChair Preprint no. 10400},

  year = {EasyChair, 2023}}
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