Facial recognition system to control the entry and exit of employees

Abstract

Facial recognition has become the most accurate institutional identification method compared to other biometric systems, it involves an automatic algorithm process that verifies and recognizes the identity of the person based on their facial characteristics. It consists of improving security, data control and institutional regulation. The purpose of the project was to develop a facial recognition system capable of controlling and recording the Entry/Exit (I/O) of employees of Bluefields Indian & Caribbean University (BICU). It is based on a qualitative approach in which the fulfillment of the operational functionalities of the system is defined and a case study was carried out to evaluate the fulfillment of the objectives. The OpenCV library for facial recognition was incorporated with the LBPH function and Python as the source of the programming language, using the prototype model. The resulting product was a facial recognition system, based on machine learning, capable of recording the I/O of BICU university employees, where each employee registered in the system is identified by facial features.