Face Recognition Based Automatic Attendance Management System
Ronika Paul, Rony Tom · Zenodo (CERN European Organization for Nuclear Research) · 2023
Abstract— The aim of this study is to develop an face based automated attendance system for hostels, utilizing facial recognition technology based on the K-nearest neighbors (KNN) algorithm. One goal is to minimize the need for direct human involvement when keeping track of attendance, as this task can be arduous, time-consuming, and resource-intensive (such as when relying on manual methods that use paper). However, we do not aim to completely eliminate human interactions from this process. To improve efficiency, the proposed approach reduces the need for manual attendance recording and management. By incorporating modern technology, the system significantly reduces resource requirements while improving accuracy and reliability. The use of facial recognition technology has gained popularity in attendance management due to its ability to enhance multimedia information access and strengthen network security. The proposed system utilizes Python for image processing, feature extraction, and matching, resulting in improved human-computer interface and better system usability. Overall, the KNN algorithm provides an effective solution for face recognition in attendance management and contributes to the advancement of automated attendance systems.