Survey on Real-Time Face Mask Detector

Authors

  • Pranav KN  BE Student, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, India
  • Pramod Mahajan H  BE Student, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, India
  • Praveen V  BE Student, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, India
  • Sai Kiran  BE Student, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, India
  • Dr. M Vinoth Kumar  Associate Professor, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, India

Keywords:

Face Mask Detection, Tensor Flow, Keras, and OpenCV.

Abstract

The COVID-19 pandemic has quickly influenced our everyday lives, disrupting commerce, and movements around the world. The wearing of a mask to cover the face has become a modern normal. In the near future, several public utility providers will be asking consumers to wear masks appropriately to make use of their facilities. Face mask identification has therefore become a key factor in helping global society. Using basic Machine Learning packages such as Tensor Flow, Keras, and OpenCV, this paper offers a simpler approach to achieving this objective. The proposed method correctly recognizes the face from the image and then identifies whether or not it has a mask on it. As a surveillance task officer, a face may also be identified along with a mask in motion.

References

  1. W.H.O., “Coronavirus disease 2019(covid- 19): situation report, 205”.2020
  2. “Coronavirus Disease 2019 (COVID-19) Symptoms”, Centers for Disease Control and Prevention,2020.Online].Available:https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html. 2020.
  3. “Coronavirus — Human Coronavirus Types — CDC”, Cdc.gov, 2020. Online]. Available: https://www.cdc.gov/coronavirus/types.html. 2020.
  4. W.H.O., “Advice on the use of masks in the context of COVID-19: interim guidance”, 2020
  5. M. Jiang, X. Fan and H. Yan, “RetinaMask:A Face Mask detector”,arXiv.org,2020. Online].Available:https://arxiv.org/abs/2005.03950. 2020.
  6. B. Suvarnamukhi and M. Seshashayee, “Big Data Concepts and Techniques in Data Processing”, International Journal of Computer Sciences and Engineering, vol. 6, no. 10, pp. 712714,2018. Available:10.26438/ijcse/v6i10.712714.
  7. F.Hohman, M. Kahng, R. Pienta and D. H. Chau, “Visual Analyticsin Deep Learning: An Interrogative Survey for the Next Frontiers,” in IEEE Transactions on Visualization and Computer Graphics, vol. 25, no. 8, pp. 2674-2693, 1 Aug. 2019, doi: 10.1109/TVCG.2018.2843369.
  8. C. Kanan and G. Cottrell, “Color-to-Grayscale: Does the Method Matter in Image Recognition?”, PLoS ONE, vol. 7, no. 1, p. e29740,2012.Available:10.1371/journal.pone.0029740.
  9. Opencv-python-tutroals.readthedocs.io. 2020. Changing Colorspaces-OpenCV-PythonTutorials 1Documentation.online]Available at:https://opencvpythontutorials.readthedocs.io/en/latest/pytutorials/pyimgproc/pycolorspaces/py colorspaces.html. 2020.
  10. M. Hashemi, “Enlarging smaller images before inputting into convolutional neural network: zero-padding vs. interpolation”, Journal of Big Data, vol. 6, no. 1, 2019. Available: 10.1186/s40537-019-0263-7. 2020.
  11. S. Ghosh, N. Das and M. Nasipuri, “Reshaping inputs for convolutional neural network: Some common and uncommon methods”, Pattern Recognition, vol. 93, pp. 7994,2019. Available:10.1016/j.patcog.2019.04.009.
  12. R. Yamashita, M. Nishio, R. Do and K. Togashi, “Convolutional neural networks: an overview and application in radiology”, Insights into Imaging, vol. 9, no. 4, pp. 611-629, 2018. Available: 10.1007/s13244-018-0639-9.
  13. “Guide to the Sequential model - Keras Documentation”, Faroit.com, 2020. Online]. Available: https://faroit.com/keras-docs/1.0.1/getting- started/sequential-model-guide/. 2020.
  14. Nwankpa, C., Ijomah, W., Gachagan, A. and Marshall, S., 2020. Activation Functions: Comparison Of Trends InPracticeAndResearch For Deep Learning. online] arXiv.org. Available at: https://arxiv.org/abs/1811.03378. 2020.
  15. K. Team, “Keras documentation:MaxPooling2D layer”,Keras.io,2020.Online].Available:https://keras.io/api/layers/poolinglayers/ max pooling2d/. 2020.
  16. “prajnasb/observations”, GitHub, 2020. Online].Available:https://github.com/prajnasb/observations/tree/master/experiements/data. 2020.
  17. “Face Mask Detection”, Kaggle.com, 2020. Online]. Available: https://www.kaggle.com/andrewmvd/face-mask-detection. 2020.
  18. “TensorFlow White Papers”, TensorFlow, 2020. Online]. Available:https://www.tensorflow.org/about/bib. 2020.
  19. K. Team, “Keras documentation: About Keras”, Keras.io, 2020. On- line]. Available: https://keras.io/about. 2020.
  20. “OpenCV”, Opencv.org, 2020. Online]. Available: https://opencv.org/.2020.
  21. D. Meena and R. Sharan, “An approach to face detection and recognition,” 2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE), Jaipur,2016,pp.1-6,doi: 10.1109/ICRAIE.2016.7939462.
  22. S. Ge, J. Li, Q. Yeand Z. Luo, “Detecting Masked Faces in the Wildwith LLE-CNNs,” 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, 2017, pp. 426-434,doi:10.1109/CVPR.2017.53.W.H.O., “Coronavirus disease 2019 (covid19):situation report, 205”.2020

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

Downloads

Published

2021-03-27

Issue

Volume 8, Issue 1, March-April-2021

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Pranav KN, Pramod Mahajan H, Praveen V, Sai Kiran, Dr. M Vinoth Kumar, " Survey on Real-Time Face Mask Detector" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 1, pp.01-08, March-April-2021.