Another system employs an audio module that outputs the list of students marked as absent so that necessary arrangements can be made if the attendance has errors. Here the entry time and exit time of the students are noted. Thus, a huge amount of time and resources are conserved and attendance keeping will be a system task instead of a manually conducted one.Īn early biometric authentication system used Arduino microcontrollers to create and control automatic attendance processes. We aim at making the attendance-taking itself automatic and hands-free by employing facial recognition systems that note who is present and absent, so as to automatically update digital attendance records in real time. In some institutions, attendance taken on pen and paper are later stored as computer records in the cloud. In the present day and age, physical records become superfluous as digital databases take charge of the vast amounts of data generated within institutions. Moreover, it is time-consuming and wastes a lot of resources (such as infrastructure needs to house the records, and the stationery required to take attendance). However, the traditional pen-and-paper mode of attendance recordkeeping is very error-prone. Students gain significant incentives based on their attendance and may even suffer penalties if the attendance is low. In an educational institution attendance management is of great administrative importance. Keywords: Haar-Cascade classifier, Raspberry Pi, face detection, Open-CV library, attendance, real time, database, confidence This information is then tabulated and stored as a spreadsheet file with the recorded date and time as the title, in the local hard disk. A desirable result is thus output from the program which indeed is the information Present or Absent, of a particular student in the database. A confidence parameter determines the recognition accuracy between these two images. This detected faces are cropped and compared with the faces in the database. The images are acquired and faces are detected in real time. The camera used for image acquisition is Pi-Camera which is connected to the Raspberry Pi via the CSI interface (Camera Serial Interface). The facial features of the students in the class are stored in a database.

Open-CV (Computer Vision) library functions were used in implementing this project.

The SoC (System on Chip) used is Raspberry Pi 3B+. Here, we implement a time-saving method of attendance management using face recognition. It has been noticed that manual attendance management is tedious, time-consuming and error- prone. of Electronics and Communication Engineering, Mar Baselios College of Engineering and Technology, Mar Ivanios Vidya Nagar, Nalanchira, Thiruvananthapuram – 695015, Kerala – IndiaĪbstract– Attendance management is an important procedure in educational institutions.

Real time attendance