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Real Time Face Mask Detector using Machine Learning, Python, OpenCV and Keras

by Aniket Mishra, M.S. Amutha
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 8
Year of Publication: 2022
Authors: Aniket Mishra, M.S. Amutha
10.5120/ijca2022922055

Aniket Mishra, M.S. Amutha . Real Time Face Mask Detector using Machine Learning, Python, OpenCV and Keras. International Journal of Computer Applications. 184, 8 ( Apr 2022), 50-52. DOI=10.5120/ijca2022922055

@article{ 10.5120/ijca2022922055,
author = { Aniket Mishra, M.S. Amutha },
title = { Real Time Face Mask Detector using Machine Learning, Python, OpenCV and Keras },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2022 },
volume = { 184 },
number = { 8 },
month = { Apr },
year = { 2022 },
issn = { 0975-8887 },
pages = { 50-52 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number8/32352-2022922055/ },
doi = { 10.5120/ijca2022922055 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:20:59.297461+05:30
%A Aniket Mishra
%A M.S. Amutha
%T Real Time Face Mask Detector using Machine Learning, Python, OpenCV and Keras
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 8
%P 50-52
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

After the new Coronavirus disease (COVID-19) case spread rapidly in Wuhan-China in December 2019, World Health Organization (WHO) confirmed that this is a dangerous virus which can be spreading from humans to humans through droplets and airborne. As for the prevention, wearing a face mask is essentials while going outside or meeting to others  However, some irresponsible people refuse to wear face mask with so many excuses. Moreover, developing the face mask detector is very crucial in this case.  This project aims to develop the face mask detector which is able to detect any kinds of face mask. In order to detect the face mask, a YOLO V4 deep learning has been chosen as the mask detection algorithm.

References
  1. "World Health Organization (WHO)", Coronavirus disease 2019 (covid-19): situation report, vol. 96, 2020..
  2. "World Health Organization (WHO)", Advice on the use of masks in the context of COVID-19, June 2020.
  3. P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features", Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition, 2001.
  4. Wei Zhu, Qian-Liang Fu and Jun-Qi Bai, "The real-time object detection algorithm based on ORBP and cascade SVM", 2016 IEEE Advanced Information Management Communicates Electronic and Automation Control Conference (IMCEC), 2016..
  5. Hong Huo and Tao Fang, "Integration of bottom-up and top-down cues in Bayesian network for object detection", Proceedings 2013 International Conference on Mechatronic Sciences Electric Engineering and Computer (MEC), 2013.
  6. J. Redmon, S. Divvala, R. Girshick and A. Farhadi, "You only look once: Unified real-time object detection", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
  7. J. Redmon and Ali Farhadi, "YOLO9000: Better Faster Stronger", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
  8. J. Redmon and Ali Farhadi, YOLOv3: An Incremental Improvement, 2018.
  9. Yunxiang Liu, Guoqing Zhang and Yuanyuan Zhang, "Vehicle detection method based on ADE-YOLOV3 algorithm", International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS), 2019.
  10. Lecheng Ouyang and Huali Wang, "Aerial Target Detection Based on the Improved YOLOv3 Algorithm", 2019 6th International Conference on Systems and Informatics (ICSAI), 2019.
  11. Changhao Piao, Xianhao Wang and Mingjie Liu, "Pedestrian Detection Using Optimized YOLOv3 in UAV Scenario", 2019 International Conference on Intelligent Computing Automation and Systems (ICICAS), 2019.
  12. Jintao Jiang, Ming Yang, XinPo Wang and Zhengguan Wu, "Auto White Balance Algorithm Based on Digital Camera", 2011 International Conference on Internet Technology and Applications, 2011.
  13. R. C. Gonzalez and R. E. Woods, Digital Image Processing, AddisonWesley, Publishing Company, Inc., 1992.
  14. X. Liu, M. Pedersen, C. Charrier and P. Bours, "Can image quality enhancement methods improve the performance of biometric systems for degraded face images?", Colour and Visual Computing Symposium (CVCS), 2018.
  15. M. O. Oloyede, G. P. Hancke and H. C. Myburgh, "Improving face recognition systems using a new image enhancement technique hybrid features and the convolutional neural network", IEEE Access, vol. 6, pp. 75181-75191, 2018.
  16. Shiming Ge, Jia Li, Qiting Yel and Zhao Luo, "Detecting Masked Faces in the Wild with LLE-CNN s", IEEE Conference on Computer Vision And pattern recognition, 2017.
Index Terms

Computer Science
Information Sciences

Keywords

Covid-19 Pandemics Face Recognition Detectors Real Time systems Production Facilities Classification algorithms

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