Face Recognition based Attendance Management System Using Haar cascade classifier and Pattern Histogram Algorithm.

Abstract

In this digital era, face recognition system plays a vital role in almost every sector. Face recognition is one of the mostly used biometrics. It can used for security, authentication, identification, and has got many more advantages. Despite of having low accuracy when compared to iris recognition and fingerprint recognition, it is being widely used due to its contactless and non invasive process. Furthermore, face recognition system can also be used for attendance marking in schools, colleges, offices, etc. This system aims to build a class attendance system which uses the concept of face recognition as existing manual attendance system is time consuming and cumbersome to maintain. And there may be chances of proxy attendance. Thus, the need for this system increases. This system consists of four phasesdatabase creation, face detection, face recognition, attendance updation. Database is created by the images of the students in class. Face detection and recognition is performed using HaarCascade classifier and Local Binary Pattern Histogram algorithm respectively. Faces are detected and recognized from live streaming video of the classroom. Attendance will be mailed to the respective faculty at the end of the session. Technology used : -open CV (Open source Computer Vision) -Python – tkinter GUI interface . The cropped images are then stored as a database with respective labels. The features are extracted using LBPH algorithm.