keywords: Biometric, fingerprint, optical scanner, Arduino software, digital counter
This research project developed a unique biometric fingerprint scanner applied in the monitoring of students attendance to class. The Students Monitor Fingerprint Biometric System (SMFBS) captures the fingerprint using a unique scanner, enrolls the image, stores the data, verifies the data, and uses it to authenticate the students. The fingerprint scanner used in this device implements the optical method to capture the fingerprint ridges and valleys. The enrolled fingerprint data is stored in micro secure digital (SD) cards. The stored fingerprint data is used to verify and authenticate a user. The SMFBS incorporates a digital counter which logs the student attendance to class using Arduino software. A printout of the students log presents each students attendance to class report indicating frequency of attendance, each attendance clock in and clock out time, and percentage attendance to class for each lecture. The developed device monitors the students’ attendance to class for lectures and laboratory practical demonstrations. In line with the university regulations, students who did not meet the minimum required number of attendance to class will not be allowed to take the examination for the referenced course. The SMFBS eliminates the possibility of a student signing for other students, a habit very prevalent within the present school environment. The developed device precision and speed in enrolling and verifying a user is effective and efficient. This is an innovation that will compel students to attend lectures leading to an improvement in the standard of education in the higher institutions of learning.
Ashraf E 2014. Design and implementation of biometric access control system using fingerprint for restricted area based on gabor filter. Computer Science Department, Menofyia University, Egypt, pp. 81-83. Brindha S & Rajalakshmi M 2013. Biometric based secured authentication in mobile web services. College of Technology and Engineering, Pollachi, Tamilnadu, 3: 71-74. Jain AK, Maio D, Maltoni D & Prabhakar S 2003. Handbook of Fingerprint Recognition, Springer, New York, pp. 131-135. Jianjiang F 2007. Combining minutiae descriptors for fingerprint matching. Pattern Recognition, 342-347 Kadry S & Smaili M 2010. Wireless attendance management system based on Iris Recognition. Scientific Res. and Essays, 5(12): 1428-1435. Lee W, Cho S, Choi H & Kim J 2017. Partial fingerprint matching using minutiae and ridge shape features for small fingerprint scanners. Elsevier Expert Systems with Applications, 87: 183-198. Oduah UI 2014. Application of the photorefractive effect of lithium niobate in the development of a fingerprint scanner with unique sensitivity. Int. J. Comp. & Electrical Engr., l6(6): 824-829. DOI: 10.7763/IJCEE.2014.V6.829. Ogbanufe O & Kim DJ 2018. Comparing fingerprint based biometrics authentication versus traditional authentication methods for e-payment. Elsevier Decision Support Systems, 106: 1-14. Peng S, Jie T, Qi S & Xin Y 2007. A novel fingerprint matching algorithm based on minutiae and global statistical features. IEEE Conference, 27-29. Ross A, Shah J & Jain AK 2007. From template to images reconstructing fingerprints from minutiae points. IEEE Transactions, 33: 72-77. Shehu V & Dika A 2011. Using Real Time Computer Vision Algorithms in Automatic Attendance Management Systems. Proceedings of the ITI 2010 32nd Int. Conf. on Information Technology Interfaces, Cavtat, Croatia, pp. 21-24. Subramaniam H, Hassan M & Widyarto S 2013. Bar Code Scanner Based Student Attendance System (SAS). Jurnal TICOM., 1(3): 173-177.