Smart Attendance Monitoring System using Facial Recognition

All Standard institutes of learning place high priority on class attendance that if the criteria is not met by the student, the student will not be granted access to sit for his/her examination conducted by the school. This makes class attendance an important activity for the student. Over the years, class attendance has been conducted manually and is still taking place currently in almost 80% of Nigerian Universities. Manual monitoring of attendance by the university's lecturer has become a hectic one for most lecturers and students. With the advancement of technology, manual marking of student’s attendance has been replaced by biometric concepts. Though many researchers have made provisions on some biometric functions like fingerprint scanner, iris recognition, hand and finger geometric. In this paper we will propose a facial recognition concept as a means of verification in marking student’s attendance and store it into the database once verified. The system made use of a dlib library OpenCv library in successfully carrying out facial recognition. Images are read into directory, and these images are encoded so as to generate 128 facial measurements like distances between the nose, ear, and eyebrow etc. This encodings will be used in making comparisons with images read from camera or from live streaming videos in other to find best matches. For the real time attendance system, we created a web application using python flask. Here we used bootstrap framework for frontend design, python as the programming language and Mysql for database design