Face Recognition using Haar Cascade and Local Binary Pattern Histogram in OpenCV

One of the most unique features that a human body can possess is the Face. This feature can be used to create a system that uniquely differentiates among different people. Face Recognition is one such system that detects a particular face by facial features. In contrast to the traditional methods of collecting attendance by calling out students' names by the teachers in a university/school or marking it in the registers at the main gate of any organization, this one consumes less time, effort, is more efficient, and also is a contactless method of doing the same. In this paper, we worked on a model that uses facial recognition technique to mark students’ attendance in an automated attendance management system using the Haar cascade classifier and LBPH algorithm. This one-time generation of dataset and face detection from the existing recognized images in this proposed system, is a more accurate and more improved system to collect attendance, thus leaving behind the tedious manual task.