Performance of COVID face mask detection based on SVM algorithm using OpenCV DNN as preprocessing model

Jiangtao Fan

doi:10.1117/12.2639377

27 June 2022 Performance of COVID face mask detection based on SVM algorithm using OpenCV DNN as preprocessing model

Jiangtao Fan

Proceedings Volume 12253, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022); 122530S (2022) https://doi.org/10.1117/12.2639377
Event: Second International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022), 2022, Qingdao, China

Abstract

As COVID-19 became a pandemic in the world, wearing a mask has become one of the best measures to prevent the spread of the epidemic, so face mask recognition in public places has become a very important part of controlling the epidemic. This paper mainly tests the performance of the OpenCV DNN preprocessing model (OpenCV DNN + SVM) based on the SVM algorithm model in the face mask recognition dataset. The dataset I use is from Kaggle called COVID Face Mask Detection Dataset. This dataset contains 503 face images with masks and 503 face images without masks. I test the performance of using OpenCV DNN + SVM and using only the SVM algorithm to evaluate this study by setting a control experimental group. In this study, it was found that using OpenCV DNN + SVM, the accuracy of ROI parameters and SVM parameters can reach 93.06% and F1score can also reach 93.06% without a lot of adjustment. The accuracy rate can only reach 68.31%, and the F1score reaches 68.31%. Findings suggest that the method using OpenCV DNN + SVM can achieve slightly better results in the COVID Face Mask Detection Dataset, and can perform better than only using the SVM algorithm. In addition, using OpenCV DNN preprocessing model based on the SVM algorithm plays an important role in feature extraction in face mask recognition. If the developer does enough parameters tuning, the accuracy will also increase.

Citation Download Citation

Jiangtao Fan "Performance of COVID face mask detection based on SVM algorithm using OpenCV DNN as preprocessing model", Proc. SPIE 12253, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022), 122530S (27 June 2022); https://doi.org/10.1117/12.2639377

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KEYWORDS

Facial recognition systems

Data modeling

Detection and tracking algorithms

Performance modeling

Image processing

Neural networks

Feature extraction

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