Face Recognition Door Locking System Using Matlab

Face recognition is an important biometric technology used for secure access control systems. This project presents a Face Recognition Door Locking System using MATLAB, designed to provide a reliable and contactless method of authentication. The system captures facial images using a webcam and processes them using image processing techniques. The implementation involves two main stages: training and recognition. In the training phase, images of authorized users are collected, pre-processed, and features are extracted using Principal Component Analysis (PCA). In the recognition phase, a live image is captured, processed, and compared with stored data using Euclidean distance to identify the user. If a match is found, the system grants access by displaying “Door Open”; otherwise, it denies access with “Access Denied.” The proposed system is simple, cost-effective, and efficient, eliminating the need for traditional methods like keys and passwords. It demonstrates the practical application of face recognition technology and can be further enhanced for real-time and hardware-based implementations.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-10
DOI
https://doi.org/10.5281/zenodo.19496343
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Face Recognition Door Locking System Using Matlab

International Journal for Research In Science & Advanced Technologies
Zenodo (CERN European Organization for Nuclear Research)
Biometric Identification and Security
article

Face Recognition Door Locking System Using Matlab

International Journal for Research In Science & Advanced Technologies
article en

Abstract

Face recognition is an important biometric technology used for secure access control systems. This project presents a Face Recognition Door Locking System using MATLAB, designed to provide a reliable and contactless method of authentication. The system captures facial images using a webcam and processes them using image processing techniques. The implementation involves two main stages: training and recognition. In the training phase, images of authorized users are collected, pre-processed, and features are extracted using Principal Component Analysis (PCA). In the recognition phase, a live image is captured, processed, and compared with stored data using Euclidean distance to identify the user. If a match is found, the system grants access by displaying “Door Open”; otherwise, it denies access with “Access Denied.” The proposed system is simple, cost-effective, and efficient, eliminating the need for traditional methods like keys and passwords. It demonstrates the practical application of face recognition technology and can be further enhanced for real-time and hardware-based implementations.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 3%
Biometric Identification and Security
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