Ofualagba GodswillOmijie OsasOrobor AndersonIbhadode OseikhuemenOdiete Etse2024-04-192024-04-192018-09-13Ofualagba Godswill, Omijie Osas, Orobor Anderson, Ibhadode Oseikhuemen, Odiete Etse. Automated Student Attendance Management System Using Face Recognition. International Journal of Educational Research and Information Science. Vol. 5, No. 4, 2018, pp. 31-37.2381-6104https://www.researchgate.net/profile/Ise-Orobor/publication/327671423_Automated_Student_Attendance_Management_System_Using_Face_Recognition/links/5b9dbdaea6fdccd3cb5a775a/Automated-Student-Attendance-Management-System-Using-Face-Recognition.pdfhttps://repository.fupre.edu.ng/handle/123456789/69Journal ArticleAttendance management system is a necessary tool for taking attendance in any environment where attendance is critical. However, most of the existing approach are time consuming, intrusive and it require manual work from the users. This research is aimed at developing a less intrusive, cost effective and more efficient automated student attendance management system using face recognition that leverages on cloud computing (CC) infrastructure called FACECUBE. FACECUBE takes attendance by using IP camera mounted in front of a classroom, to acquire images of the entire class. It detect the faces in the image and compares it with the enrolled faces in the database. On identification of a registered face on the acquired image collections, the attendance register is marked as present otherwise absent. The system is developed on Open Source image processing library hence, it is not vendor hardware nor software dependent.enArticle