Automated Student Attendance System using Fingerprint Recognition

Sifatnur Rahman (), Mahabur Rahman () and Md Mijanur Rahman ()

Edelweiss Applied Science and Technology, 2018, vol. 2, issue 1, 90-94

Abstract: The project work aims at designing a student attendance system which could effectively manage attendance of students of the department of Computer Science and Engineering at Jatiya Kabi Kazi Nazrul Islam University. In this project work, attendance is marked after students biometric identification. For student identification, a fingerprint recognition based identification system is used. Fingerprint features are considered to be the best and fastest method for biometric identification. These features are more secure to use and unique for every person that dont change in ones lifetime. Fingerprint recognition is a mature field today, but still identifying individual from a set of enrolled fingerprints is a time taking process. It was very necessary to improve the fingerprint identification system for implementation on large databases, e.g. of an institute or a country. In this project, the minutiae algorithm is used to develop the identification system which is faster in implementation than any other available today in the market. The proposed automated attendance system based on fingerprint recognition was tested on a class of student fingerprint databases and achieved significant results for taking an attendance of the students of the Department of Computer Science and Engineering. The proposed system has been implemented using C# programming paradigm platform.

Keywords: Attendance System; Biometric Features; Fingerprint Recognition; Identification; Verification. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://learning-gate.com/index.php/2576-8484/article/view/232/134 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ajp:edwast:v:2:y:2018:i:1:p:90-94:id:232

Access Statistics for this article

More articles in Edelweiss Applied Science and Technology from Learning Gate
Bibliographic data for series maintained by Melissa Fernandes ().