AUTOMATED EMPLOYEE MONITORING SYSTEM (The ProetorJ

Abstract

The goal of the "Automated Employee Monitoring System" is to modernize the current manual system by utilizing computerized equipment and software. This web application can store and access employee data efficiently and prevent redundant entries. The project aims to use facial recognition algorithms to identify and track employees, determining if they are present and working at their desks. The report examines various techniques for facial recognition, including image processing steps such as preprocessing, segmentation, and feature extraction. The software is developed using artificial neural networks, which are particularly useful for feature extraction and detection in character recognition. The system begins by preprocessing the captured image, followed by filtering, segmentation, resizing, and feature extraction. The feedforward process through the network then yields an output matrix, allowing for the identification of the recognized character. The programming language used for the end product of the algorithms is Python.