The week's pick
Reseach Article
Face Mask Detection System for Safety Assurance in Nuclear Power Facilities from Harmful and Hazardous Substance using Convolutional Neural Network and Image Processing
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 186 - Number 47 |
| Year of Publication: 2024 |
| Authors: Satya Ranjan Panda, Anuradha Rani Choudhury, Ashis Kumar Mishra |
10.5120/ijca2024924130
|
Satya Ranjan Panda, Anuradha Rani Choudhury, Ashis Kumar Mishra . Face Mask Detection System for Safety Assurance in Nuclear Power Facilities from Harmful and Hazardous Substance using Convolutional Neural Network and Image Processing. International Journal of Computer Applications. 186, 47 ( Nov 2024), 14-20. DOI=10.5120/ijca2024924130
Abstract
This research develops a computer vision-based system to detect face masks in nuclear power plants, ensuring compliance with safety regulations . The system employs image processing techniques to enhance and preprocess images from surveillance cameras, which are then fed into a Convolutional Neural Network (CNN) model for classification . The CNN model is trained on a large dataset of images collected from various power plant scenarios, achieving high accuracy in detecting individuals with or without face masks . The system detects mask-wearing individuals in real-time, enabling prompt action to ensure personnel safety and compliance . This automated system reduces manual monitoring efforts, enhances overall safety, and supports compliance with regulations . The proposed system demonstrates the effectiveness of CNN-based image processing in face mask detection, offering a reliable solution for nuclear power plants and potential applications in other industries
References
- https://en.wikipedia.org/wiki/Nuclear_power_plant
- https://en.wikipedia.org/wiki/Convolutional_neural_network
- Kumar, B. A., & Bansal, M. (2023). Face mask detection on photo and real-time video images using Caffe-MobileNetV2 transfer learning. Applied Sciences, 13(2), 935
- Sheikh, B. U. H., & Zafar, A. (2024). Untargeted white-box adversarial attack to break into deep learning based COVID-19 monitoring face mask detection system. Multimedia Tools and Applications, 83(8), 23873-23899.
- Sheikh, B. U. H., & Zafar, A. (2023). RRFMDS: rapid real-time face mask detection system for effective COVID-19 monitoring. SN Computer Science, 4(3), 288.
- Kashyap, G. S., Sohlot, J., Siddiqui, A., Siddiqui, R., Malik, K., Wazir, S., & Brownlee, A. E. (2024). Detection of a facemask in real-time using deep learning methods: Prevention of Covid 19. arXiv preprint arXiv:2401.15675.
- Chavda, A., Dsouza, J., Badgujar, S., & Damani, A. (2021, April). Multi-stage CNN architecture for face mask detection. In 2021 6th International Conference for Convergence in Technology (i2ct) (pp. 1-8). IEEE.
- Ding, H., Latif, M. A., Zia, Z., Habib, M. A., Qayum, M. A., & Jiang, Q. (2022). Facial Mask Detection Using Image Processing with Deep Learning. Mathematical Problems in Engineering, 2022(1), 8220677.
- Mengistie, T. T., & Kumar, D. (2021, May). Covid-19 face mask detection using convolutional neural network and image processing. In 2021 2nd International Conference for Emerging Technology (INCET) (pp. 1-7). IEEE.
- Bhadani, A. K., & Sinha, A. (2020). A facemask detector using machine learning and image processing techniques. Eng. Sci. Technol. Int. J, 1-8.
- Jignesh Chowdary, G., Punn, N. S., Sonbhadra, S. K., & Agarwal, S. (2020). Face mask detection using transfer learning of inceptionv3. In Big Data Analytics: 8th International Conference, BDA 2020, Sonepat, India, December 15–18, 2020, Proceedings 8 (pp. 81-90). Springer International Publishing.
- Islam, M. S., Moon, E. H., Shaikat, M. A., & Alam, M. J. (2020, December). A novel approach to detect face mask using CNN. In 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS) (pp. 800-806). IEEE
- https://www.kaggle.com/datasets/omkargurav/face mask-dataset
- Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C. Y., & Berg, A. C. (2016). Ssd: Single shot multibox detector. In Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part I 14 (pp. 21-37). Springer International Publishing.
- Qin, B., & Li, D. (2020). Identifying facemask-wearing condition using image super-resolution with classification network to prevent COVID-19. Sensors, 20(18), 5236.
- Bhadani, A. K., & Sinha, A. (2020). A facemask detector using machine learning and image processing techniques. Eng. Sci. Technol. Int. J, 1-8.
- Mathumitha, V., Kumar, M., Kumar, R. R., Thirumurugan, S., & Kaushik, S. (2024). Utilizing Deep Learning for Face Mask Detection. International Journal of Research in Engineering, Science and Management, 7(4), 59-63.
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