Attendance Management System Using Facial Recognition and Image Augmentation Technique

Over decades the attendance of students has been taken using methods involving paper. The limitations of this method are widely known and clearly understood, it is time-consuming, prone to errors and there is always a chance of proxy attendance. Many techniques that are implemented in today’s time are vastly unreliable and are majorly inefficient, like biometrics and Radio Frequency Identification (RFID), more importantly when there is a pandemic that majorly spreads via touch. This clearly presents an opportunity in the field of facial feature detection and face recognition. We propose an effective and modish solution to mark attendance using the face recognition technique including Haar Cascade and Local Binary Pattern Histogram algorithms. The system will recognize the face of an individual or multiple students and compare them with the predefined face encoding to make a CSV file of attendees with their details. To create the database we will use image augmentation techniques. This system can also be used to tackle the problem of fake attendance and proxies.