SISTEMA DE CONTROL DE ACCESO USANDO RECONOCIMIENTO FACIAL CON UNA RASPBERRY PI 4 Y OPENCV (ACCESS CONTROL SYSTEM USING FACIAL RECOGNITION WITH A RASPBERRY PI 4 AND OPENCV)
Resumen
El objetivo de este trabajo fue realizar un sistema de control de acceso usando reconocimiento facial para acceso a un centro de datos. Se desarrolló usando una tarjeta Raspberry Pi 4, una cámara de video y una pantalla táctil. La programación del sistema implanta el algoritmo de Viola-Jones para la detección del rostro y el reconocimiento del mismo usando funciones de OpenCV. La interfaz de usuario se muestra en la pantalla táctil. Cuando un usuario no autorizado intenta acceder al centro de datos, se transmite un mensaje de alerta de WhatsApp a un teléfono móvil. Las pruebas realizadas mostraron que la exactitud del sistema es 99.6 % y el tiempo de respuesta 400 ns. A partir de los resultados logrados el sistema puede usarse en otro tipo de instalaciones o aplicaciones de tiempo real.
Palabras Clave: OpenCV, Raspberry Pi 4, reconocimiento facial, Viola-Jones, WhatsApp.
Abstract
The objective of this work was to make an access control system using facial recognition for access to a data center. It was developed using a Raspberry Pi 4 card, a video camera and a touch screen. System programming implements the Viola-Jones algorithm for face detection and face recognition using OpenCV functions. The user interface is displayed on the touch screen. When an unauthorized user tries to access the data center, a WhatsApp alert message is transmitted to a mobile phone. The tests carried out showed that the accuracy of the system is 99.6 % and the response time 400 ns. Based on the results achieved, the system can be used in other types of installations or real-time applications.
Keywords: Face recognition, OpenCV, Raspberry Pi 4, Viola-Jones, WhatsApp.
Texto completo:
1011-1028 PDFReferencias
An, Z., Deng, W., Hu, J., Zhong, Y. & Zhao, Y. APA: Adaptive Pose Alignment for Pose-Invariant Face Recognition. IEEE Access, Vol. 7, 14653-14670, 2019.
Chen, H., Chen, Y., Tian, X. & Jiang, R. A Cascade Face Spoofing Detector Based on Face Anti-Spoofing R-CNN and Improved Retinex LBP. IEEE Access, Vol. 7, 170116-170133, 2019.
Ding, C. & Tao, D. Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based Face Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 40, No. 4, 1002-1014, 2018.
Galbally, J., Marcel, S. & Fierrez, J. Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition. IEEE Transactions on Image Processing, Vol. 23, No. 2, 710-724, 2014.
He, R., Wu, X., Sun, Z. & Tan, T. Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition.IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 41, No. 7, 1761-1773, 2019.
Huang, Z., Shan, S., Wang, R., Zhang, H. & Lao, S. A Benchmark and Comparative Study of Video-Based Face Recognition on COX Face Database. EEE Transactions on Image Processing, Vol. 24, No. 12, 5967-5981, 2015.
Juefei-Xu, F., Luu, K. & Savvides, M. Spartans: Single-Sample Periocular-Based Alignment-Robust Recognition Technique Applied to Non-Frontal Scenarios. IEEE Transactions on Image Processing, Vl. 24, No. 12, pp. 4780-4795, 2015.
Kamarol, S. K., Jaward, M. H., Parkkinen, J. & Parthiban, R. Spatiotemporal feature extraction for facial expression recognition. IET Image Processing, Vol. 10, No. 7, 534-541, 2016.
Liu, F., Zhao, Q., Liu, X. & Zeng, D. Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 42, No. 3, 664-678, 2020.
Liu, M., Jiang, H., Chen, J. & Huang, M. H. Tidal Volume Estimation Using Portable Ultrasound Imaging System. IEEE Sensors Journal, Vol. 16, No. 24, 9014-9020, 2016.
Liu, Y. F., Guo, J. M., Liu, P. H. & Lee, J. D. Panoramic Face Recognition. IEEE Transactions on Circuits and Systems for Video Technology, Vol. 28, No. 8, 1864-1874, 2018.
Lu, J., Liong, V. E., Zhou, X. & Zhou, J. Learning Compact Binary Face Descriptor for Face Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 37, No. 10, 2041-2056, 2015.
Moeini, A. & Moeini, H. Real-World and Rapid Face Recognition Toward Pose and Expression Variations via Feature Library Matrix. IEEE Transactions on Information Forensics and Security. Vol. 10, No. 5, 969-984, 2015.
Murphy, T. M., Broussard, R., Schultz, R. & Rakvic, R. Face detection with a Viola–Jones based hybrid network. IET Biometrics, Vol. 6, No. 3, 200-210, 2017.
Omidyeganeh, M., Shirmohammadi, S. & Abtahi S. Yawning Detection Using Embedded Smart Cameras. IEEE Transactions on Instrumentation and Measurement, Vol. 65, No. 3, 570-582, 2016.
Punnappurath, A., Rajagopalan, A. N. & Taheri, S. Face Recognition Across Non-Uniform Motion Blur, Illumination, and Pose. IEEE Transactions on Image Processing, Vol. 24, No. 7, 2067-2082, 2015.
Raghavendra, R., Raja, K. B. & Busch, C. Presentation Attack Detection for Face Recognition Using Light Field Camera. IEEE Transactions on Image Processing, Vol. 24, No. 3, 1060-1075, 2015.
Ranftl, A., Alonso-Fernandez, F. & Karlsson, S. Real-time AdaBoost cascade face tracker based on likelihood map and optical flow. IET Biometrics, Vol. 6, No. 6, 468-477, 2017.
Roy, H. & Bhattacharjee, D. Local-Gravity-Face (LG-face) for Illumination-Invariant and Heterogeneous Face Recognition. IEEE Transactions on Information Forensics and Security, Vol. 11, No. 7, 1412-1124, 2016.
Tai, Y., Yang, J., Zhang, Y., Luo, L. & Qian, J. Face Recognition With Pose Variations and Misalignment via Orthogonal Procrustes Regression. IEEE Transactions on Image Processing, Vol. 25, No. 6, 2673-2683, 2016.
Viola, P. & Jones, M. H-Rapid object detection using a boosted cascade of simple features. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1-9, ISBN: 0-7695-1272-0, HI, USA, 2001.
Weng, R., Lu, J. & Tan, Y. P. Robust Point Set Matching for Partial Face Recognition, IEEE Transactions on Image Processing, Vol. 25, No. 3, 1163-1176, 2016.
Xu, Y., Fang, X., Li, X., Yang, J. & You, Y. Data Uncertainty in Face Recognition. IEEE Transactions on Cybernetics, Vol. 44, No. 10, 1950-1961, 2015.
URL de la licencia: https://creativecommons.org/licenses/by/3.0/deed.es
Pistas Educativas está bajo la Licencia Creative Commons Atribución 3.0 No portada.
TECNOLÓGICO NACIONAL DE MÉXICO / INSTITUTO TECNOLÓGICO DE CELAYA
Antonio García Cubas Pte #600 esq. Av. Tecnológico, Celaya, Gto. México
Tel. 461 61 17575 Ext 5450 y 5146
pistaseducativas@itcelaya.edu.mx