Fingerprint-Based Attendance Management System

Abstract

Every educational institution or business organization has to maintain a proper record of attendance of students or employees for effective functioning of the organization. Attendance is a very important criteria which is used for various purposes ranging from record keeping, assessment of students/employees, and promotion of optimal and consistent attendance in class and/or at work. This research was motivated by the high level of impersonation experienced on a daily basis in both private and public sectors, the ghost worker syndrome which has become a menace across all tiers of government, employers concerns over the levels of absence in their workforce and difficulty in managing student attendance during lecture periods. Fingerprints are a form of biometric identification which cannot be forged and is unique, secure to use and does not change in one’s entire lifetime. This research work presents attendance management system using fingerprint technology in a university environment. It is made up of two phases namely; enrolment and authentication. During enrolment, the fingerprint of the user is captured and the unique features were extracted and stored in a database along with the users ID as a template for the subject. The unique features called minutiae points were extracted using the Crossing Number (CN) method which extracts the ridge endings and bifurcations from the skeleton image by examining the local neighborhoods of each ridge pixel using a 3 x 3 window. During authentication, the fingerprint of the user is captured again and the extracted features are compared with the ones already existing in the database to determine a match before attendance is made. The comparison was carried out using a minutiae-based matching system using minutiae score. The fingerprint-based attendance management system was implemented with Microsoft’s C# on the .NET framework and Microsoft’s Structured Query Language (SQL) Server 2005 as the backend. One hundred and seventeen attendees (staff and students) were used to test the system. The experimental result shows that the developed system is highly efficient in the verification of users fingerprint with an accuracy of 97.4%. The average execution time for the developed system was 4.29 seconds as against 18.48 seconds for the existing manual system. The result shows improved performance over the existing manual attendance management system and provides a secured attendance management system capable of preventing impersonation.