Biometric identification by means of Python and Raspberry Pi.
Keywords:
Python, Raspberry Pi, FaceID, biometrics, OpenCV.
Abstract
This article proposes one of the options for biometric identification, namely face recognition by means of (one of the most popular and modern) Raspberry Pi 4b single-board computer and using the Python programming language. A number of simulations were carried out and a user database was created.
References
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A. M. Burton, S. Wilson, M. Cowan, and V. Bruce, “Face recognition in poor-quality video: Evidence from security surveillance,” Psychological Science, vol. 10, no. 3, pp. 243–248, 1999.
S. Eum, J. K. Suhr, and J. Kim, “Face recognizability evaluation for atm applications with exceptional occlusion handling,” in Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on. IEEE, 2011, pp. 82–89.
T.-Y. Chen, C.-H. Chen, D.-J. Wang, and Y.-L. Kuo, “A people counting system based on face-detection,” in Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on. IEEE, 2010, pp. 699–702.
N. Kar, M. K. Debbarma, A. Saha, and D. R. Pal, “Study of implementing automated attendance system using face recognition technique,” International Journal of computer and communication engineering, vol. 1, no. 2, p. 100, 2012.
S. Tiwari, A. Singh, and S. K. Singh, “Can face and soft-biometric traits assist in recognition of newborn?” in Recent Advances in Information Technology (RAIT), 2012 1st International Conference on. IEEE, 2012, pp. 74–79.
S. Kostiuchko, O. Kuzmych, A. Aitouche, S. Grinyuk and O. Mekush, "Application of Parametric Sensitivity Method to Analysis of Automatic Mooring Winch with Electric Drive System," 2019 4th Conference on Control and Fault Tolerant Systems (SysTol), Casablanca, Morocco, 2019, pp. 294-299, doi: 10.1109/SYSTOL.2019.8864751.
A. Pentland and T. Choudhury, “Face recognition for smart environments,” Computer, vol. 33, no. 2, pp. 50–55, 2000. [2] R. Chellappa, C. L. Wilson, and S. Sirohey, “Human and machine recognition of faces: A survey,” Proceedings of the IEEE, vol. 83, no. 5, pp. 705–741, 1995.
C. Liu and H. Wechsler, “Evolutionary pursuit and its application to face recognition,” IEEE Transactions on Pattern Analysis & Machine Intelligence, no. 6, pp. 570–582, 2000.
A. W. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, “Content-based image retrieval at the end of the early years,” IEEE Transactions on Pattern Analysis & Machine Intelligence, no. 12, pp. 1349–1380, 2000.
A. M. Burton, S. Wilson, M. Cowan, and V. Bruce, “Face recognition in poor-quality video: Evidence from security surveillance,” Psychological Science, vol. 10, no. 3, pp. 243–248, 1999.
S. Eum, J. K. Suhr, and J. Kim, “Face recognizability evaluation for atm applications with exceptional occlusion handling,” in Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on. IEEE, 2011, pp. 82–89.
T.-Y. Chen, C.-H. Chen, D.-J. Wang, and Y.-L. Kuo, “A people counting system based on face-detection,” in Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on. IEEE, 2010, pp. 699–702.
N. Kar, M. K. Debbarma, A. Saha, and D. R. Pal, “Study of implementing automated attendance system using face recognition technique,” International Journal of computer and communication engineering, vol. 1, no. 2, p. 100, 2012.
S. Tiwari, A. Singh, and S. K. Singh, “Can face and soft-biometric traits assist in recognition of newborn?” in Recent Advances in Information Technology (RAIT), 2012 1st International Conference on. IEEE, 2012, pp. 74–79.
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Published
2021-03-30
How to Cite
Kostiuchko, S., Bahniuk , N., KuzmychО., Polishchuk, M., & Kyryliuk, L. (2021). Biometric identification by means of Python and Raspberry Pi. COMPUTER-INTEGRATED TECHNOLOGIES: EDUCATION, SCIENCE, PRODUCTION, (42), 142-146. https://doi.org/10.36910/6775-2524-0560-2021-42-20
Section
Computer science and computer engineering
