A Conceptual Model for Automated Attendance Marking System using Facial Recognition

Abstract

The project represents an automated attendance system based on face recognition using discriminative local binary pattern and local directional pattern descriptors. The proposed system involves face detection, Features extraction and matching. The face detection is to detect faces based on Viola Jones algorithm . In feature extraction stage, the discriminative local binary pattern is used for different object texture feature extraction process. The proposed method with new features retain the contrast information of image patterns. The Facial recognition (or face recognition) is a type of biometric application that can identify a specific individual in a digital image by analyzing and comparing patterns based on the data stored in database. Smart attendance is a real time face recognition used for handling day to day activities of the employees and students. In manual attendance system there are several issues like fake attendance and mistakenly marked absent by carelessness of the faculty/teachers/lectures. In order to overcome these problems we are using this smart attendance system. Here multiple faces are detected and recognized with trained with various features. The automated face attendance marking system gives accurate performance.