Abstract
This paper aims to develop a generic face detection and recognition system that will automate the process of collecting school attendance by recognizing students' frontal faces from classroom photographs. The reliability of the data collected is the biggest problem with the traditional attendance management systems. Many automated methods, such as biometric attendance, are being used. However, technical difficulties with scanning devices always affect the efficiency of such techniques. This paper employs principal component analysis approaches for face detection and OpenCV for face recognition to improve data quality and information accessibility for legitimate parties. The Python programming language was used for the development of the proposed system, while SQL was used for the development of the database that houses the information of users in the system. The new system was tested and shown to be not only safe but also protects students' identities by offering an anonymous attendance environment.
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