Automated Attendance Monitoring system using discriminative Local Binary Histograms and PostgreSQL
Akshat Kaushik, Yash Prakash Gupta, Yash Deshpande, Rupesh Chandrakant Jaiswal · Journal of Emerging Technologies and Innovative Research · 2020
The aim of this project is to design and implement an attendance monitoring system using Facial Recognition. The automatic attendance management will replace the manual method, which is time consuming. There are many bio-metric processes, in that face recognition is the best method. In this paper, an attendance updating system is created for administrative purposes. In this method the USB camera is fixed at a place and it will capture the image, the face of the person is detected, trained and then it is recognized with the database and finally the attendance is marked. There are various methods for comparing the faces. OpenCV (Open Source Computer Vision) is a ubiquitous computer vision library which sets its focus on real-time image processing and includes patent-free implementations of the latest computer vision algorithms. OpenCV 2.7 comes with a programming interface to Python. The Linear Binary Pattern Histograms (LBPH) Algorithm has been used in the proposed system for facial recognition. The database which records attendance is created using PostgreSQL.